bluuebunny/crossref_metadata_2025 huggingface dataset:
The added value of ECG‐gating for the diagnosis of myocardial infarction using myocardial perfusion scintigraphy and artificial neural networks
Authors: Gjertsson Peter , Lomsky Milan , Richter Jens , Ohlsson Mattias , Tout Deborah , Van Aswegen Andries , Underwood Richard , Edenbrandt Lars
Published: August 2006

To assess the value of ECG‐gating for the diagnosis of myocardial infarction using myocardial perfusion scintigraphy (MPS) and an artificial neural network. A total of 422 patients referred for MPS were studied using a one day 99mTc‐tetrofosmin protocol. Adenosine stress combined with submaximal dynamic exercise was used. The images were interpreted by one of three experienced clinicians and these interpretations regarding the presence or absence of myocardial infarction were used as the standard. A fully automated method using artificial neural networks was compared with the clinical interpretation. Either perfusion data alone or a combination of perfusion and function from ECG‐gated images were used as input to different artificial neural networks. After a training session, the two types of neural networks were evaluated in separate test groups using an eightfold cross‐validation procedure. The neural networks trained with both perfusion and ECG‐gated images had a 4–7% higher specificity compared with the corresponding networks using perfusion data only, in four of five segments compared at the same level of sensitivity. The greatest improvement in specificity, from 70% to 77%, was seen in the inferior segment. In the septal and lateral segments the specificity rose from 73% to 77% and from 81% to 85%, respectively. In the anterior segment, the increase in specificity from 93% to 94% by adding functional data was not significant. The addition of functional information from ECG‐gated MPS is of value for the diagnosis of myocardial infarction using an automated method of interpreting myocardial perfusion images.
The Machine Duplication Problem in a Job Shop with Two Jobs
Authors: Agnetis A. , Oriolo G.
Published: August 2006

This paper addresses a problem related to the classical job shop scheduling problem with two jobs. The problem consists in concurrently determining the best subset of machines to be duplicated and the optimal scheduling of the operations in order to minimize completion time. Such a problem arises in the tool management for a class of flexible manufacturing cells. The job shop with two jobs is first reviewed, the application of the classical search algorithm A* to this problem is discussed and its performance compared with a previous approach. The complexity of the machine duplication problem is then analysed. The problem is proved to be in general NP‐hard in the strong sense, but in a class of special cases, relevant from the applications viewpoint, it can be solved in polynomial time by a dynamic programming algorithm. A heuristic based on such an algorithm and on A* is proposed for the general problem; the results are satisfactory in terms of both efficiency and quality of the solution.
On the Use of Duality and Pricing Criteria in the Generalized‐simplex Method
Authors: Cardoso D.M. , Clímaco J.C.N.
Published: August 2006

Some results connected to the generalized‐simplex method and several of its main features are discussed. The duality information and pricing criteria of the classical simplex method will be incorporated in this new approach. An analogy between the generalized‐simplex method and the hybrid techniques (that combine interior point methods with the classical simplex method) is presented.
The Setting of Shelf Heights and the Distribution of Box Sizes in Two‐dimensional Shelf Packing
Authors: de Jong M.J. , Anderson E.J.
Published: August 2006

In this paper we explore two factors which have been relatively neglected in the study of shelf packing algorithms. Boxes arrive one by one at a bin that is shelved over its width and are placed into the shelves side by side, left‐justified. We consider the setting of the shelf heights, which needs to be decided upon before packing starts. We investigate the relationship between the number of boxes to be packed and the number of shelf heights that leads to minimal space wastage in the resulting packings. We also consider the distribution of the box sizes, for which we distinguish three types: (a) the continuous uniform distributionU(0, 1); (b) the discrete uniform distribution whereMsizes {1/M, 2/M,……,1} have equal probability of being chosen; and (c) an alternative discrete uniform distribution whereMsizes {s1,s2,……,sM} are drawn fromU(0, 1), which then each have equal probability of being chosen. In simulation studies we illustrate important differences between the three types of distribution.
Optimal Flow Control for Continuous‐time Scheduling in Flexible Manufacturing Systems
Authors: Khmelnitsky E. , Kogan K. , Maimon O.
Published: August 2006

This paper introduces a new approach to continuous‐time optimal scheduling problems for a large class of manufacturing systems. This class belongs to a make‐to‐order production environment, based on multi‐level bills of materials, flexible flow shops with setup effects and finite capacities on the shop floor. So far the setup and production planning had to be decomposed into two levels; the present model allows treating these two issues on one level, thus potentially achieving better production results. The proposed approach states the problem in terms of optimal control and investigates control strategies by means of the maximum principle for the problems with constraints on state variables. A numerical method concludes this investigation, sustaining the effectiveness of the approach on a robotic cell example.*
Towards a Framework for Visual Model Development
Authors: Chau P.Y.K.
Published: August 2006

A number of decision support systems (DSS) based on a visual interactive simulation (VIS) model have been implemented in recent years. A key component of a VIS model is the visual model. Existing VIS model development methodologies suggest methods (such as the paper prototype method) for developing a visual model. However, these methods are quite general and do not contain a framework to guide development. This paper describes a framework which combines the paper prototype method with systems concepts to develop the visual model. The proposed framework consists of eight stages. A project proof of principle example is described in which a VIS‐based DSS provides support to the owner of a company selling telephone systems.
Operationalizing the Data Banking Concept within a National Statistical and Information System: Problems and Prospects in Nigeria
Authors: Akinyosoye V.O.
Published: August 2006

The main issue raised in this paper is the role of Data Banks in the process of generating information for public administration in a country under a Federal System of Government. The conceptual underpinning is based on a data‐information‐decision construct and, an example is drawn from an effort to operationalize the concept within the National Statistical and Information System of Nigeria, a country with a relatively large public sector. The main inference from the paper is that although the availability of data from statistical agencies are necessary ingredients for national development programming, the establishment of data banks as decision support tools, is sinc qua non for success in this direction. This is particularly true of developing countries.
Heuristics from Nature for Hard Combinatorial Optimization Problems
Authors: Colorni A. , Dorigo M. , Maffioli F. , Maniezzo V. , Righini G. , Trubian M.
Published: August 2006

In this paper we try to describe the main characters of Heuristics ‘derived’ from Nature, a border area between Operations Research and Artificial Intelligence, with applications to graph optimization problems. These algorithms take inspiration from physics, biology, social sciences, and use a certain amount of repeated trials, given by one or more ‘agents’ operating with a mechanism of competition‐cooperation. Two introductory sections, devoted respectively to a presentation of some general concepts and to a tentative classification of Heuristics from Nature open the work. The paper is then composed of six review sections: each of them concerns a heuristic and its application to an NP‐hard combinatorial optimization problem. We consider the following topics: genetic algorithms with timetable problems, simulated annealing with dial‐a‐ride problems, sampling and clustering with communication spanning tree problems, tabu search with job‐shop‐scheduling problems, neural nets with location problems, ant system with travelling salesman and quadratic assignment problems.
Concurrent Engineering Design Using Interval Methods
Authors: Karni R. , Belikoff S.
Published: August 2006

Modern design practice has displaced serial approaches in favour of concurrent engineering design (CED), which takes several fields simultaneously into consideration, using interaction and iteration to proceed towards generally acceptable solutions. Concurrent design is very often based upon a mathematical model, which not only defines the properties and capabilities of a product, but also economic and production aspects, such as costs, tooling, machine loading and scheduling, and leads to some ‘optimum’ solution satisfying all requirements as closely as possible. This scenario does not reflect actual design activity. Each team member usually has a set of approximate requirements, which can be expressed as a range of admissible values of the design parameters. The aim is to resolve these demands, and determine a set of consistent parameter ranges which then define the design space. Iteration on the implied design alternatives leads to a final solution which is both ‘optimal’ and acceptable. A methodology which is suitable for this purpose is a mathematical model based on interval arithmetic or interval analysis. The intervals for a set of design parameters form a vector which physically defines a multi‐dimensional hypercube; the design problem is then studied by a procedures termed hypercube analysis.
OR Modelling for a Deregulated Electricity Sector
Authors: Read E.G.
Published: August 2006

OR's role in the New Zealand electricity sector has changed as the institutional structure has changed, and we might expect to find similar changes as the process of deregulation affects various sectors around the world. One result has been an increased demand for OR skills to perform familiar functions, such as cost minimization, as more decision‐makers become involved, and are given the incentives and the responsibility to optimize aspects which may have been ignored in the past. But there has also been a significant demand for OR to contribute to policy analyses, and to develop new approaches to facilitate the operation of the market in such a way as to give all parties incentives to optimize their own operations, and to provide those operating in the market with the tools they need to understand it, and to optimize their own interaction with it.
Assessing the Impact of Operating Constraints and Operating Policy on the Reliability Level of a Generation System
Authors: Lekane T. , Gheury J. , van Hecke J.
Published: August 2006

This paper presents a chronological stochastic method for evaluating the reliability of a generation system, taking operating considerations into account. A sequential Monte Carlo production simulation is used to evaluate the risk level associated with the chronological operation of the system over a year. The approach is based on a combination of a weekly deterministic unit commitment and an hour‐by‐hour simulation of the system response to unit outages that are not yet known at the beginning of the week. It enables to deal with important aspects in actual system operation: time dependent constraints, energy limited units and start‐up delays of thermal units. It can be used to assess the influence of the operating constraints and the operating policy on the reliability level of a generation system. The method is applied to a test case related to a single system and extended to a second text case involving two interconnected systems sharing their operating reserve.
Assessing Decisions on Multiple Uses of Water and Hydroelectric Facilities
Authors: Lyra C. , Castro R. , Ferreira L.R.M.
Published: August 2006

Hydroelectric systems no longer stay aside from conflicts in the use of water and facilities. As water and good sites become scarce, negotiation on multiple uses of hydro resources and sharing of costs and gains is a need. This paper gives an overview of quantitative tools designed to facilitate settlement of contentions in Brazilian hydroelectric systems. Two case studies are discussed, addressing scheduling policies for different utilities operating on the same stream and the operation of hydroplants when a variety of other users step into the scene. A framework of multiple criteria optimization is adopted in both cases, with solution approaches and computation engines tailored for each problem.
A Multiple Objective Linear Programming Approach to Power Generation Planning with Demand‐Side Management (DSM)
Authors: Martins A.G. , Coelho D. , Antunes H. , Clímaco J.
Published: August 2006

The optimization of an economic indicator has traditionally been the sole objective function of mathematical programming models for power generation expansion planning. Recently, however, other evaluation aspects, such as environmental concerns, were also given an explicit role as objective functions in mathematical models. Models become thus more realistic so that decision makers are able to grasp the inherent conflicts and trade‐offs among the distinct objectives in selecting a best compromise plan. A significant change in the planning processes has also occurred concerning new planning methodologies integrating demand‐side management (DSM) techniques, in an attempt to change the levels and forms of electricity use by the consumers. This paper presents a multiple objective linear programming model for power generation expansion planning incorporating DSM. The objective functions are the total expansion cost, the environmental impact associated with the installed power capacity and the environmental impact associated with the energy output. DSM is included by modelling it as a new generating group along with the generating alternatives from the supply side. Five categories of constraints are considered related to the reliability of the supply system, the availability of the generating units, the capacity of the DSM‐equivalent generating group, the total capacity installed throughout the planning period, the pollutant emissions. Some results are presented derived by using an interactive method, aimed at assisting decision makers in a progressive and selective search of good compromise solutions.
Optimal Banknote Replenishing Policy by an Issuing Bank
Authors: Ladany S.P.
Published: August 2006

The minimal total cost replenishing policy for legal banknotes by the Bank of Israel (a ‘Federal’ Issuing Bank) was determined in three stages: (a) the market demand for banknotes of different denominations for a planning horizon of 10 years was evaluated using regression analysis; (b) the periodic supply of the banknotes to the market was estimated from the incremental market demand and the need to replace worn out banknotes; and (c) a total cost discrete Dynamic Programming model was constructed to find the optimal ordering quantities of banknotes, under the constraints of maximal storage and maximal order size capacities.
A Comparative Analysis of Various Optimization Models for Electricity Capacity Expansion
Authors: Smith R.A. , Villegas A.M.
Published: August 2006

Several optimization models have been proposed in the literature to solve the project selection, timing and sequencing problem. Models based on dynamic programming (DP) such as embebed state DP, objective space DP, and others have been used to solve the capacity expansion problem. Also models based on mixed integer linear programming using Benders decomposition theory, and heuristic rules have been proposed to solve that problem. In this paper these models are analyzed and compared from the theoretical point of view. All the reviewed models are then compared using them to define the minimum cost expansion of the Colombian electric sector. The Colombian interconnected electric generation system has about 10,000 MW of installed capacity with a generation composition of 80% hydro‐generation plants and 20% thermo‐generation plants. the expansion planning of the system has been carried out at a national level using simulation and optimization techniques. All these techniques are reviewed and discussed in this paper. Some conclusions and recommendations are finally presented.
Performance Analysis of a Client–Server System Using Queueing Networks: A Case Study
Authors: Horikawa T. , Tanaka A. , Kino I.
Published: August 2006

Queueing networks have been widely used to evaluation performance of mainframe computer systems. In contrast, few results have been reported for modern open systems, so it was not clear whether queueing networks are useful for modern systems or not. We think this situation has partly been due to lack of handy evaluation tools. This paper presents tow tools that we developed to evaluate open system performance. On is a measuring tool that is capable of accurately obtaining the service times of system resources requested by an application transaction. The other is an estimating tool which calculates various performance measures based on queueing network models. This paper also describes a case study in which the performance of a medium‐sized UNIX client–server system (up to 24 clients) is estimated using the tools and these estimates are then compared with experimental results. The estimates closely agree with the measured results and are accurate enough for practical applications. Based on this, we conclude that queueing network models are also useful for modern systems.
Partially‐Linear Transportation Problems, Obtained by Means of Absolute Value Functions
Authors: Dangalchev C.A.
Published: August 2006

Nonlinear transportation problems may be successfully used to model problems in economics, due to the nonlinear relationship between quantities and the real cost for their transportation. In this paper we consider transportation problems with two‐piece linear functions on arcs (which may be nonconvex), where the nonlinearity is represented by absolute value functions. A necessary and sufficient condition for local optimality is given and an algorithm for solving these problems is suggested.
The Efficiency Analysis of Skyscrapers Based on the Inner Traffic
Authors: Li M. , Fushimi M.
Published: August 2006

The effectiveness of investment on a skyscraper exists as a problem because a substantial portion of the space may be necessary for the inner traffic. We theoretically analyze the influence of such factors of a building as the shape, the height, etc. on the effectiveness of investment.
Feasible Sequential Decisions and a Flexible Lagrangean‐Based Heuristic for Dynamic Multi‐Level Lot Sizing
Authors: Ingold T. , Gröflin H.
Published: August 2006

We propose an extended model for dynamic multi‐level lot sizing with general acyclic product structure and unconstrained resources (MLUR, including additional constraints on lot sizes and cumulative production. These allow for interactive decisions and flexible planning sequences. For three types of decisions we examine the space of feasible decisions, the main part being dedicated to single‐product decisions, In order to be able to solve the single‐product problems with the algorithm by Chen et al.(Journal of Global Optimization, 4(4, 397–413. We focus on the case where the decision space can be given by upper and lower bound constraints on lot sizes and cumulative production. We establish a characterization of this case as well as sufficient conditions of wide applicability and give algorithms to compute the bounds. As an application, we formulate a Lagrangean‐based heuristic using a primal procedure with flexible planning sequence. Extensive testing on classical MLUR problems shows consistent improvement in solution quality compared with other heuristics.
Production Control of a Flexible Manufacturing System in a Job Shop Environment
Authors: Hansmann K‐W. , Hoeck M. , Hansmann K.‐W.
Published: August 2006

This paper provides an application oriented analysis of local search procedures for Operation Scheduling and Shop Floor Management of a major German manufacturer of cigarette machines. The heuristics applied are the Threshold‐ and Simulated Annealing‐Algorithm considering Job Shop as well as embedded FMS production features. In this context a new neighbourhood search technique is developed, which is based on a small set of local neighbourhoods and is flexible with respect to the performance measurements of production control. By this approach the scheduling, loading and workload allocation problems of a production facility consisting of an embedded FMS and a conventional Job Shop can be solved simultaneously.
Transport Infrastructural Investment Project Rankings under Quasi‐uniform Resource Allocating Constraint, Assisted by a Multicriterion Analysis Process
Authors: Nandor Kiss L. , Tanczos K.
Published: August 2006

Consider: (1) a finite set of transport infrastructural investment projects (TIIP) previously analysed by the decision maker(s) in the framework of some multicriterion analysis process in order to reveal a preference (i.e. precedence)—relation pair set (PRS) and; (2) the ranking problem of this TIIP subject to the PRS constraints and a quasi‐equal financial expenses rhythm‐constraint. We outline an algorithmic aid of this ranking problem exploiting deliberately the non‐mutual congruity between an incomplete PRS and resulting hierarchical structures.
Synchronized Scheduling Method in Manufacturing Steel Sheets
Authors: Tamura R. , Nagai M. , Nakagawa Y. , Tanizaki T. , Nakajima H.
Published: August 2006

An efficient two‐stage algorithm has been developed to solve a large‐scale multiobjective scheduling problem in steel sheets production. The heuristic algorithm is a blend of operator's know‐how and a mathematical solution. The two‐stage procedure consists of a rough and detailed scheduling step based on order groping. It enables us to do synchronized scheduling for a multistage manufacturing process as well as to reduce the number of combinations. In addition, the dynamic programming supports efficient calculation. The scheduling system contributes to better‐designed schedules and drastic reduction of scheduling time.
Fine‐tuning a Tabu Search Algorithm with Statistical Tests
Authors: Xu J. , Chiu S.Y. , Glover F.
Published: August 2006

Tabu Search is a metaheuristic that has proven to be very effective for solving various types of combinatorial optimization problems. To achieve the best results with a tabu search algorithm, significant benefits can sometimes be gained by determining preferred values for certain search parameters such as tabu tenures, move selection probabilities, the timing and structure of elite solution recovery for intensification, etc. In this paper, we present and implement some new ideas for fine‐tuning a tabu search algorithm using statistical tests. Although the focus of this work is to improve a particular tabu search algorithm developed for solving a telecommunications network design problem, the implications are quite general. The same ideas and procedures can easily be adapted and applied to other tabu search algorithms as well.
A New Mixed Integer Formulation for the Maximum Regret Problem
Authors: Mausser H.E. , Laguna M.
Published: August 2006

The minimax regret solution to a linear program with interval objective function coefficients can be found using an algorithm that, at each iteration, solves a linear program to generate a candidate solution and a mixed integer program to find the corresponding maximum regret. This paper presents a new formulation for the latter problem that exploits the piecewise linear structure of the cost coefficients. Computational results indicate that this yields a stronger formulation than the previous approach.
Operations research and semantic control: application to advanced traffic management
Authors: García‐Ortiz A. , Amin S.M. , Wootton J.R.
Published: August 2006

Operations Research (OR) is well known for the plethora of tools and techniques it offers to address complex and sometimes non‐intuitive problems. In this paper we propose the use of the semantic control paradigm as a framework for the development of advanced traffic management systems (ATMS), and show how the tools afforded to us by OR can be applied within this framework to solve problems in traffic management. A brief overview is given of the scope of problems addressed by OR, and of the structure of a semantic control system. This is followed with an example showing the application of artificial neural networks and shortest path algorithms to the problem of estimating highway traffic volume and the subsequent allocation of traffic to maintain road capacity.
A simultaneous route and departure time choice equilibrium model on dynamic networks
Authors: Ziliaskopoulos A.K. , Rao L.
Published: August 2006

In this paper, we are concerned with modeling dynamic networks, when drivers simultaneously optimize their departure time and route choice. We state equilibrium conditions and propose a simulation‐based model that can solve large networks accounting for many realities of actual networks. The main components of the model are a time‐dependent shortest path algorithm for fixed arrival times and a traffic simulator. The proposed model has the potential to realistically capture user decisions when arrival time based origin–destination tables are easier to obtain than the departure time based ones e.g. in the morning peak and in special events. Two solution methodologies are designed and tested: the first emulates users day‐to‐day dynamic behavior and does not guarantee convergence; the second is a heuristic approach that adjusts link travel times and always converges to an equilibrium solution, although not at the desired level of schedule delay. Computational experiments on a small street network are presented.
A model for aeromedical routing and scheduling
Authors: Ruland K.S.
Published: August 2006

The Aeromedical Airlift Wing of the United States Air Force is responsible for the transportation of military personnel in need of specialized medical treatment to and from various military hospitals. Over eight million active and retired personnel, spouses and dependents benefit from the system. The system operates under a variety of regulations to ensure timely service and safe operation of the aircraft. This paper presents a model of the system to assist the route planners in generating solutions minimizing patient inconvenience. This is achieved by assigning patients to sequences of aircraft while minimizing layovers.
A continuous‐time integrated model for discrete control of production flows in a multi‐level bills of material environment
Authors: Kogan K.
Published: August 2006

An integrated dynamic model for discrete production scheduling and continuous capacity expansion is presented in this paper. The modeled manufacturing system, based on multi‐level bills of materials, is characterized by flexible machines with negligible setups and production rates fixed for the current capacity. Make‐to‐stock formulation of the problem is studied and optimal behavior of the system is determined with the help of the maximum principle. A fast time‐decomposition algorithm is suggested to locate the optimal solution.
An effective procedure for the distribution of magazines
Authors: Artto K.A. , Pylkkänen E.
Published: August 2006

The article provides theoretical and empirical findings on developing an effective procedure for magazine single copy distribution. Considerations of determinants of demand are provided, emphasizing the importance of price and seasonality. A relative adjustment formula for stockout corrections is introduced, applicable in connection with normally distributed demand. The main contribution is a new demand forecasting and supply decision model, taking explicitly into account price and seasonality. The applicability and potential economic benefits are shown by giving results from an extensive empirical test in the Finnish single copy market.
Genetic algorithms to schedule container transfers at multimodal terminals
Authors: Kozan E. , Preston P.
Published: August 2006

Optimising the container transfer schedule at the multimodal terminals is known to be NP‐hard, which implies that the best solution becomes computationally infeasible as problem sizes increase. Genetic Algorithm (GA) techniques are used to reduce container handling/transfer times and ships' time at the port by speeding up handling operations. The GA is chosen due to the relatively good results that have been reported even with the simplest GA implementations to obtain near‐optimal solutions in reasonable time. Also discussed, is the application of the model to assess the consequences of increased scheduled throughput time as well as different strategies such as the alternative plant layouts, storage policies and number of yard machines. A real data set used for the solution and subsequent sensitivity analysis is applied to the alternative plant layouts, storage policies and number of yard machines.
Multicriteria distribution network planning using simulated annealing
Authors: de Leão M.T. Ponce , Matos M.A.
Published: August 2006

The classical long‐range distribution network planning problem involves deciding network investments to meet future demand at a minimum cost while meeting technical restrictions (thermal limits and maximum voltage drop). The decision whether to construct facilities and branches leads to a mixed integer programming problem with a large number of decision variables. The great deal of uncertainty associated with data that cannot be modeled using probabilistic methods leads to the use of fuzzy models to capture the uncertainty. In addition, several criteria must be taken into account that is resulting in the problem being fuzzy multiobjective. The combinatorial nature of the problem limits the use of traditional mathematical tools to limited size problems. This contribution presents a methodology that generates a sample of efficient solutions for the fuzzy multiobjective problem, based on a meta‐heuristic, simulated annealing (SA). The results obtained with this approach are shown to be satisfactory compared to other methods under similar conditions.
Regulated quality diffusion under quadratic costs
Authors: Liu J. , Nam S‐H.
Published: August 2006

We study how to regulate quality processes so as to attain a desirable target. The effect of the regulation varies in a random fashion due to disturbances. The interaction between regulatory actions and outcomes is termed quality diffusion. In this paper, we address a specific version of such diffusion known as a mean‐reverting process (also termed Ornstein Uhlenbeck process). The total production cost includes both a quadratic cost of quality deviations, and a linear cost of production control. Assuming that both regulation and quality processes are continuously reviewed, an optimal quality regulation policy is sought to minimize the total production cost over a finite horizon. The optimal regulation is found to be a surge‐discharge control that can be characterized by a triplet including a discharge time, a stopping time, and a discharge function. The surge‐discharge control is easy to be implemented for a variety of applications. Computational algorithms for the optimal control are developed.
A project evaluation system in the state economic information system of China An operations research practice in public sectors
Authors: Zhang X‐S. , Cui J‐C.
Published: August 2006

Operations Research (OR) methodology and its mathematical models have been widely accepted as management means in China, not only in industry and agriculture, but also in non‐profit organizations, including the governmental departments and institutions. In this paper, we introduce an OR practice in the State Information Center (SIC) of China. The task is to design and develop a system, the Project Evaluation System, for SIC to manage investments in the various parts of the State Economic Information System of China (SEIS). It is a decision support system with various OR models and algorithms combined together as the core part of the system. Data Envelopment Analysis is used to evaluate the relative efficiencies of the sub‐systems of the SEIS and the Analytic Hierarchy Process methodology is adopted to form the decision process. To allocate further investment to the sub‐systems, an investment prediction model for non‐profit organizations was formulated which is in a format of a parametric linear programming problem. This new OR model can be applied in many decision problems in economy and finance. We also discuss in this paper the experience summed up from our practice.
Transmission planning for Indian power grid: a mixed integer programming approach
Authors: Chaturvedi R. , Bhattachary K. , Parikh J. , Bhattacharya K.
Published: August 2006

The paper presents a modeling framework to analyze some important issues associated with operation planning of a power system. Major activities involved in operations planning of large integrated power systems are considered simultaneously to ensure optimal utilization of generation and transmission capacity. The model also examines optimal transmission expansion plans vis‐à‐vis fuel supply issues. A mixed integer programming model is developed for this purpose and the Indian power system considered. Specific emphasis is on spatial transmission expansion plan for the existing Indian inter‐state transmission grid and new transmission links, coordinated operation of the isolated regional grids and system benefits accruing from transmission expansion, enhanced fuel production and supply rescheduling to ensure efficient operation of various generating stations.
Translational polygon containment and minimal enclosure using mathematical programming
Authors: Milenkovic V.J. , Daniels K.
Published: August 2006

A new algorithm is given for the two‐dimensional translationalcontainmentproblem: find translations forkpolygons which place them inside a polygonal container without overlapping. Both the polygons and the container can be non‐convex. The algorithm is based on mathematical programming principles. The containment algorithm is generalized to solveminimal enclosureproblems: find the minimal area enclosing square or minimal area enclosing rectangle forktranslating polygons. The containment algorithm consists of new algorithms forrestriction,evaluation, andsubdivisionof two‐dimensional configuration spaces. Restriction establishes lower bounds through relaxation and the solution of linear programs. Evaluation establishes upper bounds by finding potential solutions. Subdivision branches, when necessary, by introducing a cutting plane. The algorithm shows that either the upper bound of the objective (overlap) is exactly zero or the lower bound is greater than zero. Hence, it gives an exact solution to the containment problem. Experiments show that new containment algorithm clearly outperforms purely geometric containment algorithms. For data sets from the apparel industry, it can solve containment for up to ten non‐convex polygons in practice. An implementation of the algorithm given in this paper has been licensed by Gerber Garment Technologies, the largest provider of textile CAD/CAM software in the US, and they are incorporating it into an existing CAD/CAM software product.
MCDA: a constructivist approach to the management of human resources at a governmental agency
Authors: Ensslin L. , Dutra A. , Ensslin S.R.
Published: August 2006

In the context of a concern with a self sustaining system for the management of Human Resources, those responsible for the Coordination of Human Resources at the Governmental Agency ‘Secretaria de Administração do Estado de Santa Catarina’ (SEA) have decided to use a Constructivist Multicriteria Decision Aid Approach (MCDA) to help them identify the most convenient courses of action for the achievement of the proposed goals. The present paper shows both the development of an MCDA model and the process used for action generation and assessment.
Learning scheduling control knowledge through reinforcements
Authors: Miyashita K.
Published: August 2006

This paper introduces a method of learning search control knowledge in schedule optimization problems through application of reinforcement learning. Reinforcement learning is an effective approach for the problem faced by the agent that learns its behavior through trial‐and‐error interactions with a dynamic environment. Nevertheless, reinforcement learning has a difficulty of slow convergence when applied to the problems with a large state space. The paper discusses the case‐based function approximation technique, which makes reinforcement learning applicable to the large scale problems such as a job‐shop scheduling problem. To show effectiveness of the approach, reinforcement learning is applied to acquire search control knowledge in repair‐based schedule optimization process. Preliminary experiment results show that repair‐action selection made by learned search control knowledge succeeded in improving scheduling quality efficiently.
New dominance criteria for the generalized permanent labelling algorithm for the shortest path problem with time windows on dense graphs
Authors: da Cunha C.B. , Swait J.
Published: August 2006

This paper describes state‐dominance criteria for the Generalized Permanent Labelling Algorithm (GPLA) for solving the Shortest Path Problem with Time Windows on dense graphs, which occurs as a subproblem of a vehicle routing problem. These criteria markedly improve its performance. One of the criteria we propose is based on a backward‐looking test at the destination node. The other is a dominance test for the label being treated, which avoids the generation of successor states from dominated labels. Both are possible due to a new order of storing the labels for a given node within each bucket: the generated temporary labels are stored and later treated in decreasing service time order and increasing cost order. This order of label treatment, allied with the suggested dominance criteria, results in a significant time execution performance improvement with respect to the basic dense‐graph GPLA.
Modelling congestion in closed queueing networks
Authors: Pollett P.K.
Published: August 2006

We will consider the problem of identifying regions of congestion in closed queueing networks with state‐dependent service rates. A particular queue will be called a bottleneck if the number of customers in that queue grows without bound as the total number of customers in the network becomes large. We will review methods for identifying potential bottlenecks, with a view to controlling congestion. We will see that the problem of identifying bottlenecks can be reduced to one of finding them in an isolated subnetwork with suitably modified routing intensities. Several special cases will be studied, illustrating a range of behaviour. For example, it is possible for a subnetwork to be congested, yet each queue in that subnetwork is not strictly a bottleneck.
Applying combinatorial optimization metaheuristics to the golf scramble problem
Authors: Dear R.G. , Drezner Z.
Published: August 2006

One typical golf tournament format is termed a ‘Scramble,’ comprised of four‐person teams. The participants are rank‐ordered into four equally sized ‘flights’ based on integer‐valued handicaps determined by skill level. One participant from each flight is selected to make up a team. Of interest is the assignment of teams in an ‘equitable’ fashion, where equitable is defined as minimizing the difference between the largest and smallest sum of the handicaps. For a typical tournament of 36 teams there are over 10 124 unique assignments. Since in general there are duplicate handicap values, the number of ‘equivalent’ assignments is reduced (but still very large). Various heuristics are explored for efficiently identifying an optimal or near optimal solution. These include descent heuristics, simulated annealing, tabu search, and genetic algorithms. Genetic algorithms outperform other heuristics by taking advantage of the problem structure.
Reduced game property of the Egalitarian Non‐k‐Averaged Contribution (EN k AC‐) value and the Shapley value
Authors: Namekata T. , Driessen T.S.H.
Published: August 2006

The Egalitarian Non‐k‐Averaged Contribution (ENk AC‐) value for TU‐game represents the equal division of the surplus of the total profits, given that each player is already allocated his individual contribution specified by worths of coalitions of size k. This paper deals with the axiomatic characterization of the ENk AC‐value on the class of cooperative games with a fixed player set as well as a variable player set. The latter axiomatization involves a consistency axiom in terms of the reduced games. The ENk AC‐value is the unique value on the class of cooperative games with a variable player set which possesses the relative invariance under strategic equivalence, the equal treatment property and the reduced game property for two types of reduced games. We also propose a new reduced game in terms of which the Shapley value is axiomatized.
Worst‐case performance of critical path type algorithms
Authors: Singh G. , Zinder Y.
Published: August 2006

The critical path method remains one of the most popular approaches in practical scheduling. Being developed for the makespan problem this method can also be generalized to the maximum lateness problem. For the unit execution time task system and parallel processors this generalization is known as the Brucker–Garey–Johnson algorithm. We characterize this algorithm by introducing an upper bound on the deviation of the criterion from its optimal value. The bound is stated in terms of parameters characterizing the problem, namely number of processors, the length of the longest path, and the total required processing time. We also derive a similar bound for the preemptive version of the Brucker– Garey–Johnson algorithm.
Using official ratings to simulate major tennis tournaments
Authors: Clarke S.R. , Dyte D.
Published: August 2006

While the official Association of Tennis Professionals (ATP) computer tennis rankings are used to seed players in tournaments, they are not used to predict a player's chance of winning. However, since the rankings are derived from a points rating, an estimate of each player's chance in a head to head contest can be made from the difference in the players' rating points. Using a year's tournament results, a logistic regression model was fitted to the ATP ratings, to estimate the chance of winning as a function of the difference in rating points. Once the draw for a tournament is available, the resultant probabilities can be used in a simulation to estimate each player's chance of victory. The method was applied to the 1998 Men's Wimbledon, 1998 Men's US Open and the 1999 Men's Australian tennis championships.
A polynomial time algorithm to detect PQI interval orders
Authors: The A.N. , Tsoukiàs A. , Vincke P.
Published: August 2006

Let S be a PQI preference structure on a finite set A, where the relations P, Q, I stand for ‘strict preference’, ‘weak preference’ and ‘indifference,’ respectively. Two specific preference structures: PQI semi orders and PQI interval orders, have been considered and characterised recently in such a way that is possible to associate to each element of A an interval such that P holds when one interval is completely to the right of the other, I holds when one interval is included to the other and Q holds when one interval is to the right of the other, but they do have a non empty intersection (Q medelling the hesitation). While the detection of a PQI semiorder is straightforward, the case of the PQI interval order is more difficult as the theorem of existence consists in a second‐order formula. The paper presents an algorithm for detecting a PQI interval order and demonstrates that it is backtracking free. This result leads to a matrix version of the algorithm which can be proved to be polynomial.
Pseudomonas aeruginosasepsis in an adult horse with enteric Salmonellosis
Authors: Johns Imogen C. , Jesty Sophy A. , James Frances M.
Published: August 2006

Objective:To report a case of enteric Salmonellosis andPseudomonas aeruginosabacteremia in an adult horse.

Case summary:A 7‐year‐old mare presented for signs of acute abdominal pain. Exploratory laparotomy allowed surgical correction of right dorsal displacement of the large colon with a 180° volvulus at the cecocolic ligament. Postoperatively, the mare developed fevers, leukopenia, and diarrhea.Salmonella newportwas cultured from the feces andP. aeruginosafrom 2 consecutive blood cultures. The mare responded well to intensive medical therapy.

New or unique information provided:Bacteremia associated with colitis is unusual in an adult horse, although the percentage of animals that may be bacteremic is unknown. The bacteria isolated,P. aeruginosa, a common pathogen of other sites in the horse, has not, to our knowledge, been previously reported as a cause of bacteremia and septicemia in an adult horse.
Back to the Future? A Critical Commentary on the 2003 U.S. National Standard Certificate of Live Birth
Authors: Kirby Russell S , Salihu Hamisu M
Published: August 2006

ABSTRACT:  Vital statistics documents for the United States have been revised approximately decennially throughout the past century. In this commentary we review the contents of the 2003 revision of the national standard certificate of live birth, focusing on changes from the certificates in use nationally since 1989, and identifying strengths and weaknesses of key data elements. Additional federal‐state partnership funding is imperative to support the transition to the new standard certificates, and to ensure a focus on data quality at the state and national levels. (BIRTH 33:3 September 2006)
Efficacy of Rimonabant and Other Cannabinoid CB1 Receptor Antagonists in Reducing Food Intake and Body Weight: Preclinical and Clinical Data
Authors: Carai Mauro A. M. , Colombo Giancarlo , Maccioni Paola , Gessa Gian Luigi
Published: August 2006

The present paper focuses on the different lines of evidence indicating that cannabinoid CB1 receptor antagonists, including the prototype rimonabant, reduce food intake and body weight in laboratory animals. Recent clinical surveys demonstrated that rimonabant significantly reduced body weight also in overweight/obese humans. Treatment with rimonabant was associated with a beneficial effect on different metabolic parameters and cardiovascular risk factors linked to overweight. The data reviewed in this paper suggest that cannabinoid CB1 receptor antagonists may constitute a novel class of drugs potentially effective in the treatment of obesity‐related disorders.