bluuebunny/crossref_metadata_2025 huggingface dataset:
Drama Theory
Authors: Bryant James
Published: January 2011

Drama theory explains how people resolve differences. It overcomes the paradoxes created by attempting to be instrumentally rational in multiparty situations where there is interdependence in the choices made by those involved. It is a positive and a nonquantitative approach: assumptions about participants are taken to be empirical statements and numerical utilities are not used. It contrasts with alternative derivatives of metagame analysis, which seek “solutions” to an interaction within a structure where players' preferences and options are fixed. Drama theory recognises that confrontations are practically resolved by appealing to the wider context within which the “small world” of formal game theoretic models is set. It has been applied to situations involving collaboration or conflict and provides a language for people to represent how they would like matters resolved and what they intend if a solution cannot be found. The pressures that each party faces can systematically be explored, and guidance on the management of the interaction can be developed. Confrontations in international relations, corporate alliances, departmental coworking, and human relations management have all been analyzed using drama theory. Analyses can also be used to create focused role‐play training exercises permitting participants to rehearse new roles or relationships.
Effective Application ofGRASP
Authors: Festa Paola , Resende Mauricio G. C.
Published: January 2011

A greedy randomized adaptive search procedure (GRASP) is an iterative multistart metaheuristic for difficult combinatorial optimization. Each GRASP iteration consists of two phases: a construction phase, in which a feasible solution is produced, and a local search phase, in which a local optimum in the neighborhood of the constructed solution is sought. Since 1989, GRASP has been applied to a wide range of combinatorial optimization problems, ranging from scheduling and routing to drawing.

In this article, we cover the literature where GRASP is applied to scheduling, routing, logic, partitioning, location, graph theory, assignment, manufacturing, transportation, telecommunications, biology and related fields, automatic drawing, power systems, and VLSI design.
Eliciting Subjective Probabilities from Individuals and Reducing Biases
Authors: Mihajlovits Bethany H. , Merrick Jason R. W.
Published: January 2011

Thinking in terms of probabilities is not easy and we tend to use rather primitive cognitive techniques to make such assessments. These techniques are called
heuristics
. Heuristics are simple and intuitive but tend to result in probabilities that are biased. This article reviews the problems associated with probability elicitation and methods for improving such assessments.
Evacuation Planning
Authors: Regnier Eva
Published: January 2011

Evacuation planning encompasses a broad set of decisions that sometimes mean the difference between life and death. The Operations Research (OR) community can bring important strengths to evacuation planning. Some of OR's powerful modeling tools are readily applicable to evacuation decisions. In addition, OR researchers and practitioners have expertise in framing complex, multiobjective public decisions to produce solutions that can be implemented in the real world. This article outlines areas in which OR has contributed and has the potential to contribute, as well as challenges to the application of OR tools and approaches in evacuation planning.
Fairness and Equity in Societal Decision Analysis
Authors: Keller L. Robin , Wang Yitong , Feng Tianjun
Published: January 2011

This article provides a brief theoretical and empirical introduction to the examination of fairness and equity in societal decision analysis.
Fast and Frugal Heuristics
Authors: Bertel Sven , Kirlik Alex
Published: January 2011

Cognitive heuristics are fundamental to human judgment and decision making. Often described as rules of thumb that are used in lieu of optimal procedures (e.g., when resources are limited, or knowledge is incomplete), cognitive heuristics may also be understood as essential psychological mechanisms that guide information search and produce decisions by effectively and efficiently exploiting information structures in the environment. This article describes a selection of simple but powerful, task‐specific, fast and frugal heuristics (FFHs) as suggested by Gigerenzer, Todd, and the ABC Research Group. Underlying assumptions related to concepts of ecological rationality are presented, as are basic mechanisms of, and research into the validity of FFHs.
Finite Population Models—Single Station Queues
Authors: Jayaraman Raja , Matis Timothy I.
Published: January 2011

A finite population queueing model consists of service requests generated by finite number of customers handled by either a single or multiple number of servers. There are several practical applications of finite‐source models including the machine–repairman model, multiprocessor systems, time‐sharing systems, telecommunication models, vacation models, reliability models, and so on. In this article, we review several applications of finite‐source models, and analyze the classical machine–repairman model in steady state to discuss related performance measures. Variations to the underlying characteristics and assumptions of this model lead to the development and analysis of a broader class of queueing problems motivated by these applications, for which we present extensions and suggestions for further reading.
Forecasting for Inventory Planning under Correlated Demand
Authors: Baykal‐Gürsoy Melike , Erkip Nesim K.
Published: January 2011

In this article, we review inventory planning approaches in order to find out demand‐forecasting requirements. We consider single‐ and multi‐item supply chains under stationary and nonstationary, correlated demand. We also examine Martingale model of forecast evolution (MMFE), which is a way for modeling forecasts. We then summarize forecasting procedures that will be helpful in realizing the aforementioned inventory models.
Foundations of Simulation Modeling
Authors: Kin Wai , Chan Victor
Published: January 2011

Simulation modeling is an important step of a simulation study. It concerns with the creation of an efficient simulation model as accurate as needed to mimic the behavior of the underlying system and to reproduce useful observations for subsequent analysis. This introductory article discusses three main simulation modeling methods: discrete‐event simulation, continuous simulation, and agent‐based simulation. In particular, three discrete‐event simulation modeling paradigms are introduced: event scheduling, process interaction, and activity scanning. Several modeling issues are exemplified by a simple single‐server queueing system and a slightly more complex multiple‐server finite capacity queueing system with impatient customers. Continuous simulation is briefly discussed to draw the differences between discrete‐event and continuous simulations. Simulating emergent behavior as a common purpose of agent‐based simulation is demonstrated by a classic game of life model and a variation model. Monte‐Carlo simulation and other simulation modeling formalisms are briefly highlighted.
Generating Homogeneous Poisson Processes
Authors: Pasupathy Raghu
Published: January 2011

We present an overview of existing methods to generate pseudorandom numbers from a nonhomogeneous Poisson process. We start with various definitions of the nonhomogeneous Poisson process, present theoretical results (sometimes with a proof) that form the basis of existing generation algorithms, and provide algorithm listings. Whenever available, we also provide links to sources containing computer codes. With the intent of guiding users seeking an appropriate algorithm for a given setting, we emphasize computationally burdensome operations within each algorithm. Our treatment includes both one‐dimensional and two‐dimensional Poisson processes.
Genetic Algorithms
Authors: Pelikan Martin
Published: January 2011

Genetic algorithms are stochastic optimization methods inspired by natural evolution and genetics. Over the last few decades, genetic algorithms have been successfully applied to many problems of business, engineering, and science. Because of their operational simplicity and wide applicability, genetic algorithms are now playing an increasingly important role in computational optimization and operations research. This article provides an introduction to genetic algorithms as well as numerous pointers for obtaining additional information.
German Operations Research Society (
GOR
) (
G
esellschaft Für Operations Research)
Authors: Hamacher Horst W.
Published: January 2011

The German Operations Research Society (GOR) is presented. The presentation includes a sketch of GOR's historical development and a description of its numerous activities such as professional journals, annual conferences, working groups, and awards.
Hellenic Operational Research Society
Authors: Matsatsinis Nikolaos
Published: January 2011

This paper describes the current status, the trends and challenges of the Hellenic Operations Research Society (HELORS). The profile of OR in public and private sectors, the specific role of the country's OR society and the educational opportunities are outlined. Finally, the results of a survey on OR work carried out and presented in Greece during the last 10 years are presented and the challenges that OR will face in the future are discussed.
History of Constraint Programming
Authors: Barták Roman
Published: January 2011

Constraint programming is a technology for solving combinatorial optimization problems. It appeared in the 1960s in systems such as Sketchpad, and core ideas such as arc and path consistency techniques were proposed and developed in the 1970s. The real landmark of constraint programming was in the 1980s when researchers realized that unification in logic programming is a special form of constraint solving, and constraint logic programming appeared. Since that time, many solving techniques and approaches were studied, but the core idea of constraint programming remains the same—it is a technology based on integration of search techniques with special inference techniques exploiting the structure of constraints in the problem. Constraint programming is successful in many application areas. Scheduling is probably the most prominent one, but constraints are also applied when solving problems in planning, configuration, vehicle routing, networking, bioinformatics, and so on. This article describes how constraint programming evolved since its beginnings to the current state.
The Hungarian Operations Research Society
Authors: Csendes Tibor
Published: January 2011

A short description of the Hungarian Operations Research Society is given with special attention to its history, activities, and main achievements of the recent years.
Icelandic Operations Research Society
Authors: Stefánsson Hlynur , Ásgeirsson Eyjólfur Ingi , Ólafsson Snjólfur
Published: January 2011

The Icelandic Operations Research Society was founded in 1985. It has around 100 members. The main activities are in the form of monthly meetings where OR‐related work is presented. The topics presented are from industry and academia alike and so are the members of the society. In 2006 ICORS hosted the EURO conference in Iceland. The theme of the conference was “OR for Better Management of Sustainable Development.” On the whole, the conference was a great success with 1541 delegates from 63 countries.

Introductory courses to OR are taught to approximately 250 students every year and several advanced courses are offered at undergraduate and graduate levels. There are in total five faculty positions in Iceland that are devoted to operations research. There are at least four members of ICORS that have OR/management science faculty positions in foreign universities, including Georgia Institute of Technology, London School of Business, Stanford University, and University of Atlanta. Quite a few students have completed MSc or PhD degrees in operations research from various foreign universities, mostly in North America and Europe. OR methods have been used in several significant practical projects and the main emphasis has been on fishing and the fishing industry as it is one of the backbones of the Icelandic economy.
Initial Transient Period in Steady‐State Systems
Authors: White K. Preston , Robinson Stewart
Published: January 2011

This article describes the problem of the initial transient that arises when estimating the limiting distribution of a nonterminating stochastic process. Concepts are explored with references to simple M/M/1 queueing model with an artificially induced initial bias. A range of solution methods have been proposed and here we explore two such approaches, graphical and heuristic. We also demonstrate how these methods might be combined. Results from test problems consistently show that truncation of output data from a single long run is more economical than the replication/deletion approach for nonterminating simulations.
The Naturalistic Decision Making Perspective
Authors: Nemeth Christopher , Klein Gary
Published: January 2011

The naturalistic decision making (NDM) approach seeks to understand human cognitive performance by studying how individuals and teams choose among alternatives in real‐world settings. Unlike laboratory studies, NDM research captures human interactions with actual work settings that are typically uncertain, complex, fluid, and time‐pressured. The NDM approach emphasizes the role of experience in making it possible for individuals to quickly categorize situations in order to make effective decisions. Models of behavior that have resulted from these studies inform research and performance in high hazard work settings such as revisions of military doctrine, training that is focused on decision requirements, and the development of information technologies to support cognitive work.
Job Shop Scheduling
Authors: Posner Marc E.
Published: January 2011

This article contains a basic survey of job shop scheduling. It provides a description of two common formulations and a discussion of solution methods. Also included are extensions, applications, and future research directions.
The Law and Economics of Risk Regulation
Authors: Coglianese Cary
Published: January 2011

Law plays a central role in the management of risk in society. The rules adopted by regulatory agencies now affect nearly every facet of the economy, and as such regulation has motivated a substantial body of academic research. Law and economics research on regulation has, first, demonstrated the normative justification for governmental intervention in the marketplace based on the concept of market failure. Second, political economy research on regulation has shown how, as a positive matter, interest groups, political movements, and public pressure affect the stringency of such regulation, sometimes more than any normative rationale for regulation. Third, risk regulation research has clarified the available normative principles that can guide the selection of regulatory stringency, from the zero‐risk principle to cost‐benefit balancing. Finally, the law and economics literature on risk regulation offers lessons about the form or design of regulatory instruments, from traditional “command‐and‐control” standards to more innovative possibilities, such as market‐based instruments or management‐based regulation.
Maintenance Management
Authors: Leung Kit‐Nam Francis
Published: January 2011

The purpose of this article is to introduce to engineers, health‐care workers, and others who bear the responsibility for decision making in the general area of equipment maintenance, the potential benefits that can accrue to an organization by an examination of maintenance problems from a management science (MS) perspective. MS is concerned, to a large extent, with the construction of mathematical models of problem situations whereby alternative actions can be assessed, and the best identified.

Research into production technologies should consider maintenance. the significance and complexity of maintenance in modern production and manufacturing systems indicate that maintenance should be viewed as an increasingly important area of study and research.
Markov Renewal Processes
Authors: Ziya Serhan
Published: January 2011

A Markov renewal process is a vector valued counting process that keeps track of the number of certain types of events associated with a stochastic process. It is a generalization of a renewal process in that a Markov renewal process with a single‐dimensional state representation is a renewal process. In this article, we first define Markov renewal sequences, which are at the core of Markov renewal processes. Then, we give a formal description of Markov renewal processes and provide a number of examples where these processes appear.
Mass Customization
Authors: Parlaktrk Ali K. , Swaminathan Jayashankar M.
Published: January 2011

Mass customization aims to provide individually customized products with near mass production efficiency. We give examples of different types of mass customization. We then discuss the benefits that make mass customization attractive. This includes ability to charge price premiums, stronger relations with customers, better market understanding, and ability to operate without finished‐goods inventories. Mass customization leads to some challenges due to the variability it introduces to a firm's operations. We discuss some enablers of mass customization that can help firms overcome these challenges.
Metaheuristics for Stochastic Problems
Authors: Hvattum Lars Magnus , Esbensen Eystein Fredrik
Published: January 2011

A large number of publications have been written about metaheuristics and their use in solving deterministic optimization problems. As metaheuristic techniques become more widespread in the production of decision support systems, it is clear that they also need to cope with problems, based on real‐world applications, that contain noise and uncertainty. An increasing amount of work is being put into the study of metaheuristics for stochastic problems, and into how metaheuristics must be adapted to efficiently handle different sources of stochasticity. We give examples of how metaheuristics have been used to solve stochastic problems, thereby illustrating the additional considerations that are required in this context.
MINLPSolver Software
Authors: Bussieck Michael R. , Vigerske Stefan
Published: January 2011

In this article we give a brief overview of the start‐of‐the‐art in software for the solution of mixed integer nonlinear programs (MINLP). We establish several groupings with respect to various features and give concise individual descriptions for each solver. The provided information may guide the selection of a best solver for a particular MINLP problem.
Modeling Uncertainty in Optimization Problems
Authors: Philpott Andy
Published: January 2011

We introduce some standard approaches to modeling uncertainty in optimization problems formulated as mathematical programs. We distinguish between probabilistic and nonprobabilistic models that are each illustrated using simple examples drawn from problems of optimal electricity generation.
Models and Basic Properties
Authors: Henrion René
Published: January 2011

This chapter provides an introduction into basic models and properties of probabilistic constraints. Models are distinguished according to structural assumptions about the underlying system of inequalities and the distribution of the random parameter. Resulting analytical properties like continuity and convexity are discussed for different settings. Since the crucial features of probabilistic programming are hidden in the constraints, we disregard in this introduction, the connection with the objective function which goes basically along the common lines of nonlinear optimization.
Monte Carlo Simulation as an Aid for Deciding Among Treatment Options
Authors: Shechter Steven
Published: January 2011

Patients and their physicians are often faced with difficult choices among multiple treatment options, including the proper timing of them. Moreover, these decisions must be made under uncertainty of what outcomes may arise overtime. For various reasons, randomized controlled trials are often not feasible for helping determine the best course of therapy in these situations. Instead, researchers are increasingly turning to Monte Carlo simulation as another means for helping estimate the costs and benefits of different treatment options. We describe the motivation for this methodology, key elements of a treatment simulation model, as well as limitations and challenges in developing these models.
Materials Requirements Planning
Authors: Benton, W.C.
Published: January 2011

Material Requirements Planning (MRP) is a material planning methodology developed in the 1970's making use of computer technology. MRP provide the ability to proactively manage inventory levels and material flows through a manufacturing facility. The primary features of MRP are the creation of material requirements via exploding the bills of material, and time‐phasing of requirements using posted average lead times. MRP II was developed as the second generation of MRP and it features the closed loop system: production planning drives the master schedule which drives the material plan which is the input to the capacity plan. MRP determines when components items are needed and scheduling them to be ready at that time, no earlier or later.
Multicommodity Flows
Authors: Vaidyanathan Balachandran , Ahuja Ravindra K.
Published: January 2011

The multicommodity flow problem is a generalization of the minimum cost network flow problem. In this problem, several commodities governed by their own network flow constraints share the same underlying network. Given the supplies and demands of the different commodities, the shared capacity of each arc in the network, and cost of flow of each commodity on each arc, the objective is to determine the flow that minimizes the total cost. The multicommodity flow problem has been extensively applied to solve problems in areas such as transportation, telecommunications, and scheduling. In this article, we introduce the multicommodity flow problem, outline some of its applications, and describe efficient methods to solve the problem.
Neuroeconomics and Game Theory
Authors: Stallen Mirre , Sanfey Alan G.
Published: January 2011

Many of our decisions are made in the context of highly complex social interactions. By combining neuroscientific measures with formal models of game theory, researchers have gained insight into the mechanisms underlying social decision making. Early findings from this interdisciplinary effort have already begun to show how reasoning about the intentions of others is important for interactive behavior, how the reward system of the brain is directly involved in cooperation and social exchange, and how the experience of emotions plays a vital role in successful decision making. The neuroeconomic approach to social decision making offers exciting potential to move beyond speculation about the processes that determine our decisions in interactive contexts, and to extend our knowledge about the functioning of the human brain.
Omega Rho International Honor Society for Operations Research and Management Science
Authors: Rogers David F.
Published: January 2011

Founded in 1976 and formally a part of INFORMS since 1998, Omega Rho International Honor Society for operations research and management science is a member of the Association of College Honor Societies and a foundation for excellence in operations research and management science disciplines. Primarily designed for honoring our best students and faculty through chapters established at universities, Omega Rho also sponsors the
Omega Rho Distinguished Lecture
at INFORMS Annual Meetings and select International Meetings, and provides annual support for the INFORMS Doctoral Student Colloquium and other select student‐related events. Chapter expansion around the globe to honor deserving students effectively is an ongoing emphasis.
Operations Research Models for Cancer Screening
Authors: Alagoz Oguzhan , Ayer Turgay , Erenay Fatih Safa
Published: January 2011

Early diagnosis through screening is an effective means of decreasing the death rate from cancer, the second leading cause of death in the US, since most cancers are now curable if detected early. On the other hand, the interventional procedures that result from detected abnormalities (both false and true positives) during screening and the significant cost of population‐based screening of asymptomatic individuals require a careful analysis of the benefits and risks of screening in both utility and economic terms. In this article, we summarize the studies applying Operations Research (OR) tools to investigate issues related to cancer screening. In particular, we review OR studies considering cancer screening that are either briefly described or not mentioned in previous review articles. We classify relevant literature by cancer type including breast cancer, colorectal cancer, and cervical cancer. We also discuss several issues for future research in cancer screening.
Operations Research Tools for Addressing Current Challenges in Emergency Medical Services
Authors: Henderson Shane G.
Published: January 2011

Emergency medical service (EMS) providers face a host of significant challenges, including traffic congestion, increasing call volumes, hospital diversion (i.e., emergency departments at hospitals not allowing ambulances to deliver patients to them), and increasing transfer times at emergency departments. Many of these challenges can be attacked through an application of operations research (OR) techniques in conjunction with EMS expertise. The purpose of this article is to outline some of the key challenges and potential OR‐based remedies, and to discuss in detail one such remedy that has various names including “system‐status management” and “move up.”
Non‐Expected Utility Theories
Authors: Bordley Robert F.
Published: January 2011

In this article nonexpected utility theories are reviewed, which focuses on four controversial axioms underlying Savage's subjective expected utility theory. For each axiom, we present practical concerns raised by each axiom along with Savage's defense of that axiom. We then discuss efforts to address these problems that are consistent with Savage's axioms (which we refer to asparadigm preserving) as well as efforts to address these problems that relax or violate Savage's axioms (which we refer to asparadigm shifting.) We conclude that this tension between paradigm‐preserving versus paradigm‐shifting approaches to address problems in Savage's formulation has been invaluable.
Optimization Problems in Passenger Railway Systems
Authors: Caprara Alberto , Kroon Leo , Toth Paolo
Published: January 2011

This article describes the main optimization problems that are faced in the planning of a passenger railway system, from the definition of the routes and frequencies of the trains in the railway network to the construction of the duties and the rosters for drivers and conductors. These problems are presented in the order in which they are faced in practice, illustrating what they are aimed at, and how they are solved by mathematical programming techniques. The article also briefly illustrates recent advances in producing “robust” (i.e., fault‐tolerant) solutions for these problems, and in the application of optimization methods for real‐time recovery of railway systems.
Perfect Information and Backward Induction
Authors: Kaminski Marek M.
Published: January 2011

Backward induction (BI) is defined for extensive‐form games of perfect information. The relation of BI to Nash equilibrium, the concept of incredible threat, and subgame perfect equilibrium is described. Variants of the procedure include cutting long subgames or cutting any subset of disjoint subgames. The discussion of criticisms is focused on the incorrect predictions of BI in games such as Centipede. An example of the incorrect application of BI concludes the article.
Evaluations of Single‐ and Repeated‐Play Gambles
Authors: Wedell Douglas H.
Published: January 2011

Choices and evaluations of risky prospects often violate norms of expected utility theory and the underlying normative principles of rational decision‐making. However, when risky prospects are represented as being repeatedly instantiated, choices and evaluations often change to conform more closely to the long‐run perspective reflected in normative models. Differences between responses for single and repeated gambles have been analyzed normatively, explored empirically, and evaluated theoretically. Normative analyses have argued both for and against changing behavior for single and repeated gambles. Empirically, shifts in behavior for single and repeated risky prospects are found to be common, stronger when outcomes are perceived as fungible, and stronger when the repeated outcome distribution is displayed. Furthermore, these shifts have been found to occur in both laboratory and real‐world settings and have been considered a possible moderator of violations of expected utility theory. A variety of theoretical explanations are posited to explain this behavior, including those that emphasize consequences of loss aversion as well as those that implicate alternative bases for evaluating single and repeated cases.
Pricing and Lead‐Time Decisions
Authors: Pekgün Pelin
Published: January 2011

This article presents an introductory review of centralized and decentralized models for the determination of price and lead‐time decisions in monopolistic and competitive settings.
Quantum Command and Control Theory
Authors: Forsythe Steve
Published: January 2011

This article presents results of a Johns Hopkins University Applied Physics Laboratory (JHU/APL) effort on the fundamental theory of C2. A standard method for course of action (COA) selection is the weighted numerical comparison (WNC) method. There are numerous issues with the WNC method. One of these issues is that the expected results are frequently used to select a course of action (COA). The Quantum C2 Theory, like the physics‐based quantum theory, treats outcomes not as point estimates but rather as probability distributions. Understanding and employing these probability distributions can aid commanders in shaping and selecting courses of actions that are the best trade‐off between mission success and risk. Several alternatives to WNC are presented which mitigate some of the issues with WNC and provide improved support for the commander's COA selection.
Risk Assessments and Black Swans
Authors: Aven Terje
Published: January 2011

Risk assessments are used to identify hazards/threats, assess their consequences, and describe risk. The assessments provide a basis for evaluating whether risk is tolerable or acceptable and for choosing the most effective and efficient risk reduction measure. The issue raised in this article is to what extent the assessments are able to reveal and adequately describe risk contributions from potential “surprises” (“black swans”). We argue that the standard probabilistic‐based assessments have too narrow a perspective on uncertainties to be successful in this respect. An extended risk assessment approach, which sees beyond the probabilistic analysis, is required. The basic pillars of such an approach are outlined.
Surgery Planning and Scheduling
Authors: Erdogan S. Ayca , Denton Brian T.
Published: January 2011

Surgery planning and scheduling systems play a critical role in the efficient matching of supply and demand for surgery. Competing performance measures and a number of complicating factors make surgery planning and scheduling challenging. Operating room (OR) managers must consider uncertainty in the duration of surgery and other critical activities, the arrival of unexpected urgent add‐on patients, and cancellations on the day of surgery while efficiently managing a variety of human and technical resources. Surgery schedules must be designed to balance competing performance criteria such as patient waiting time as well as idle time and overtime for both the OR team and other personnel. This article presents an introduction to surgery scheduling, a literature review, a small example, and a description of some of the important open challenges.
Why Traditional Kanban Calculations Fail in Volatile Environments
Authors: Kessinger Colin , Gray Allan
Published: January 2011

Recent years have seen the extension of “kanban thinking” from the factory floor to entire supply chain networks. However, the traditional calculations used to size kanbans often perform poorly in these new environments, which are characterized by longer leads times and higher demand volatility. This article examines why that is the case, and highlights many of the common pitfalls facing practitioners when implementing kanbans or reorder points (ROPs). Among the issues tackled are why “consumption‐based” reorder points are flawed in volatile environments; how companies' attempts to incorporate forecasts in kanban calculations go awry; and how confusion among alternative definitions of service level can lead to excess inventory.
Why Risk is Not Variance
Authors: Cox, Louis Anthony , Huber William A.
Published: January 2011

Variance (or standard deviation) of return is widely used to measure risk in financial investment risk analysis and mean‐variance portfolio optimization. Yet, except under very special conditions (such as normally distributed returns), mean‐variance decision making violates the principle that a rational decision maker should prefer higher probabilities of receiving a fixed gain to lower probabilities, all else being equal. Indeed, a mean‐variance decision maker who considers all prospects corresponding to some particular mean‐variance combination to be unacceptable would necessarily refuse some prospects that offer a positive probability of gain and no possibility of loss—a rule that few canny risk managers would want to live by.
“On‐The‐Spot” Modeling And Analysis: The Facilitated Modeling Approach
Authors: Franco Luis A. , Montibeller Gilberto
Published: January 2011

Since the 1980s, an alternative to the traditional “expert” mode of model‐based consultancy has been suggested, where the management scientist acts both as an analyst and as a facilitator throughout the intervention. This alternative approach usesfacilitated modelingas the main intervention tool, which requires the management scientist to carry out the whole intervention jointly with a team drawn from the client organization: from helping to structure and define the nature of the problem situation of interest, to supporting the evaluation of priorities and development of plans for subsequent implementation. This mode of engagement is particularly suitable for supporting the development of strategy, the analysis of policy issues, or the evaluation of high‐stake decisions. This article discusses the facilitative modeling paradigm in management science. Drawing on research scattered across a range of publications and domains, we provide a formal definition of facilitated modeling, examine its general characteristics, and briefly review a family of well‐established facilitated modeling approaches. We then discuss key issues to consider when designing facilitated modeling interventions, and identify some directions for future research.
Improving Packaging Operations in the Plastics Industry
Authors: Tyagi Rajesh , Bollapragada Srinivas
Published: January 2011

A large plastics company commissioned the development and use of an improved packaging system based on a simulation study to increase the capacity of its packaging operations at one of its divisions. The four bag‐ and box‐packaging stations that pack the material produced by 13 extrusion lines were causing a major bottleneck that was impacting the throughput of the plant and was resulting in significant costs due to increased outsourcing of packaging operations. A team that included the authors simulated the plant operations to show that the packaging capacity could be significantly increased through better scheduling and that there was no need to invest in additional equipment and manpower. The team then developed and implemented a packaging system with a novel scheduling system that has increased throughput capacity by 20%. In addition, the system has yielded significant cost savings because of productivity gains and reduced outsourcing of packaging operations.
Optimization for Dispatch and Short‐Term Generation in Wholesale Electricity Markets
Authors: Zakeri Golbon
Published: January 2011

While operations research is utilized across all sectors of wholesale electricity markets, it is most widely and intensely used in the generation sector. We review the operations of a wholesale electricity market and provide a detailed treatment of optimization in the generation sector.
Game‐Theoretic Methods in CounterTerrorism and Security
Authors: Bier Vicki M.
Published: January 2011

Protecting against intentional attacks on homeland security is fundamentally different from protecting against accidents or acts of nature. In particular, an intelligent and adaptable adversary may adopt a different offensive strategy in response to our protective security measures, in order to circumvent or disable them. Game theory provides a way of taking this into account analytically. Thus, security can benefit from game‐theoretic methods. This article discusses approaches for applying game theory to the problem of defending systems against attack. The results yield insights into the nature of optimal defensive investments.
Optimization and Decision Sciences (Italy)
Authors: Tadei Roberto
Published: January 2011

In this article, the history of the Italian Operations Research Society‐Optimization and Decision Sciences is presented. It was founded in 1961 and is still very active at the national and international level. For more details, please refer to
www.airo.org
.
A translocation between Xq21.33 and 22q13.33 causes an intragenic SHANK3 deletion in a woman with Phelan–McDermid syndrome and hypergonadotropic hypogonadism
Authors: Misceo D. , Rødningen O.K. , Barøy T. , Sorte H. , Mellembakken J.R. , Strømme P. , Fannemel M. , Frengen E.
Published: January 2011

Chromosome 22q13 monosomy has been described as a contiguous gene syndrome. Localized in the critical region, SHANK3 is likely to play a key role in the expression of the clinical phenotype. SHANK3 mutations have also been reported in autistic patients without a syndromic phenotype. We report on a 20‐year‐old woman with mental retardation carrying a de novo translocation between chromosome Xq21.33 and 22q13.33, associated with a duplication on Xq21.33 and deletion on 22q13.33. As a child her development was characterized by disturbed social interaction, stereotypic hand movements and ritualistic behavior and she was considered at one time to have autistic features. All these traits match the 22q13 deletion syndrome (Phelan–McDermid syndrome, OMIM 606232), likely due to the deletion overlapping the last two exons of the SHANK3 gene. Our patient harbors the smallest and most distal SHANK3 deletion described to date, yet resulting in the full spectrum of the Phelan–McDermid syndrome. In addition, she has hypergonadotropic hypogonadism with low estrogen level, high FSH level, and irregular menstruation. Intriguingly, chromosome translocations affecting the chromosome band Xq21 can result in premature ovarian failure. © 2011 Wiley‐Liss, Inc.
Rediscovery of the largest population of the freshwater pearl mussel (Margaritifera margaritifera) in the Leningrad oblast (north‐west Russia)
Authors: Ostrovsky A. N. , Popov I. Yu.
Published: January 2011

An internationally important population of the freshwater pearl mussel (Margaritifera margaritifera) was rediscovered in a small river in north‐west Russia.

A survey of visible mussels in 2008/2009 indicated an estimated population of 40 000 individuals. This is the largest population currently known in the Leningrad oblast and is comparable with the entire pearl mussel population of some western European countries.

The average density of visible mussels was 29.6 individuals m−2in the middle part of the river. In the four largest mussel beds maximum densities of 1000+ individuals m−2were recorded. Such densities are exceptional and have not been reported elsewhere in Europe during the last 100 years.

Live juvenile mussels were recorded, indicating that that this population is viable, although further investigation is required to establish its status.

Analysis of the population age structure, based on the measurement of empty shells, showed an age class distribution similar to those reported for other healthyMargaritiferapopulations.

Only two live juveniles were found. However, this is likely to be due to the survey being restricted to counts of visible mussels only, and the age structure being based on the analysis of dead shells.

The population's current status and possible reasons for its survival in this river are discussed. Conservation measures should include the construction of a fish ladder to make fish migration through the culvert possible, removal of a metal screen preventing fish migration from the upper reaches of the river to the lake, reduction of recreation activities, and providing the local children's camp with water treatment facilities. Copyright © 2011 John Wiley & Sons, Ltd.
Application of multistate models in hospital epidemiology: Advances and challenges
Authors: Beyersmann Jan , Wolkewitz Martin , Allignol Arthur , Grambauer Nadine , Schumacher Martin
Published: January 2011

Survival analysis has established itself as a major statistical technique in medical research. Applications in hospital epidemiology, however, are only beginning to emerge. One reason for this delay is that usually complete follow‐up of patients in hospital is feasible. This overview discusses where survival techniques provide additional insight into hospital epidemiology, and where they are, in fact, needed even in the absence of right‐censoring.
NMR Studies of DOXP Reductoisomerase and its Inhibitor Complex
Authors: Englert Nadine E. , Richter Christian , Wiesner Jochen , Hintz Martin , Jomaa Hassan , Schwalbe Harald
Published: January 2011

1‐Deoxy‐D‐xylulose 5‐phosphate (DOXP) reductoisomerase (EC1.1.1.267) catalyses the second step of the 2‐C‐methyl‐D‐erythritol 4‐phosphate (MEP) pathway of isoprenoid biosynthesis. The enzyme is used by most bacteria, apicomplexan parasites and the plastids of plants, but not by humans, and therefore represents an attractive target for antibacterial, antiparasitic and herbicidal compounds. Fosmidomycin, an inhibitor of DXR, has been found to be active against bacterial infections and malaria in early clinical studies. Here, we report sample optimisation, partial backbone assignment and secondary‐structure prediction of E. coli DXR by heteronuclear NMR analysis for further NMR‐aided drug discovery. Perdeuterated 15N,13C‐labelled samples were prepared under oxygen exclusion in the presence of Mg2+, NADPH and the inhibitor FR‐900098, a close derivative of fosmidomycin. 1H and 15N backbone assignment was achieved for 44 % of the primary structure, and 13C backbone assignment was achieved for 50 % of the primary structure. Comparison with previously solved crystal structures revealed that the assigned fragments were located mainly in helical regions on the solvent‐exposed surface of the enzyme. Torsion angle likelihood obtained from shift and sequence similarity (TALOS) was used for secondary structure prediction, resulting in agreement with eight available crystal structures; deviations could be observed for the catalytic loop region.
Discharge Characteristics of Pressure Swirl Atomizers
Authors: Musemic Emir , Walzel Peter
Published: January 2011

Mit Hilfe theoretischer Überlegungen und experimenteller Daten bzw. Herstellerangaben wurde eine halbempirische Berechnungsvorschrift für den Ausflusskoeffizienten von Hohlkegeldüsen vorgeschlagen und mit bekannten Beziehungen aus der Literatur verglichen. Die vorgeschlagene Berechnungsvorschrift berücksichtigt die Viskosität der Flüssigkeit und ist auch für geometrisch verschiedenartige Düsenbauformen geeignet.
Discovery of Isoerianin Analogues as Promising Anticancer Agents
Authors: Messaoudi Samir , Hamze Abdallah , Provot Olivier , Tréguier Bret , Rodrigo De Losada Jordi , Bignon Jérôme , Liu Jian‐Miao , Wdzieczak‐Bakala Joanna , Thoret Sylviane , Dubois Joëlle , Brion Jean‐Daniel , Alami Mouad
Published: January 2011

The cytotoxic activity of a series of 23 new isoerianin derivatives with modifications on both the A and B rings was studied. Several compounds exhibited excellent antiproliferative activity at nanomolar concentrations against a panel of human cancer cell lines. The most cytotoxic compound, isoerianin (3), strongly inhibits tubulin polymerization in the micromolar range. Moreover, isoerianin leads to G2/M phase cell‐cycle arrest in H1299 and K562 cancer cells, and strongly induces apoptosis. Isoerianin also disrupts the vessel‐like structures formed by human umbilical vein endothelial cells (HUVECs) in vitro, suggesting that this compound may act as a vascular disrupting agent. It clearly appears that in this compound series, the 1,1‐ethane bridge encountered in isoerianin derivatives can replace the 1,2‐ethane bridge of natural erianin with no loss of activity. This reinforces the bioisosteric replacement approach in the combretastatin series previously reported by our research group.
Fast in‐place, comparison‐based sorting with CUDA: a study with bitonic sort
Authors: Peters Hagen , Schulz‐Hildebrandt Ole , Luttenberger Norbert
Published: January 2011

State‐of‐the‐art graphics processors provide high processing power and furthermore, the high programmability of GPUs offered by frameworks like CUDA (Compute Unified Device Architecture) increases their usability as high‐performance co‐processors for general‐purpose computing. Sorting is well investigated in Computer Science in general, but (because of this new field of application for GPUs) there is a demand for high‐performance parallel sorting algorithms that fit with the characteristics of the modern GPU‐architecture. We present a high‐performance in‐place implementation of Batcher's bitonic sorting networks for CUDA‐enabled GPUs. Therefore, we assigned compare/exchange operations to threads in a way that decreases low‐performance global‐memory access and makes efficient use of high‐performance shared memory. This greatly increases the performance of this in‐place, comparison‐based sorting algorithm. Our implementation outperforms all other algorithms in our tests when sorting 64‐bit keys. It is the fastest comparison‐based GPU sorting algorithm for 32‐bit keys, being only outperformed by (non‐comparison‐based) radix sort when sorting sequences larger than 223. Copyright © 2011 John Wiley & Sons, Ltd.