bluuebunny/crossref_metadata_2025_split huggingface dataset:
Operations research and semantic control: application to advanced traffic management
Authors: García‐Ortiz A. , Amin S.M. , Wootton J.R. 
Published: August 2006

AbstractOperations 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

AbstractIn 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

AbstractThe 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

AbstractAn 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

AbstractThe 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

AbstractOptimising 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

AbstractThe 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

AbstractWe 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

AbstractOperations 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

AbstractThe 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

AbstractA 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

AbstractIn 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

AbstractThis 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

AbstractThis 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

AbstractWe 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

AbstractOne 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

AbstractThe 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

AbstractThe 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

AbstractWhile 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

AbstractLet 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

AbstractObjective: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.
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

ABSTRACTThe 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.