bluuebunny/crossref_metadata_2025_split huggingface dataset:
Disjunctive Inequalities: Applications And Extensions
Authors: Belotti Pietro , Liberti Leo , Lodi Andrea , Nannicini Giacomo , Tramontani Andrea 
Published: February 2011

AbstractWe survey some applications and extensions of disjunctive programming with special emphasis on recent developments. Specifically, after recalling the basic ingredients of disjunctive inequalities we report on recent results in the context of mixed integer linear programming. We then consider the application of disjunctive constraints both as modeling tool and cutting planes in mixed integer nonlinear programming. Finally, we discuss the application of disjunctions as branching conditions in enumerative algorithms, as opposed to the cutting approach.
Multivariate Input Modeling
Authors: Biller Bahar 
Published: February 2011

AbstractAs large‐scale discrete‐event stochastic simulation becomes a tool that is used routinely for the design and analysis of service and manufacturing systems, it is critical to develop multivariate input models that are flexible enough to capture the joint distributional properties of multivariate input processes. In this document, we review the recent advances in multivariate input modeling with focus on developing fast sampling algorithms for driving large‐scale discrete‐event stochastic simulations.
Nash Equilibrium (Pure and Mixed)
Authors: Jones Michael A. 
Published: February 2011

AbstractThis article defines and examines the Nash equilibrium solution concept for noncooperative strategic form games. Examples of canonical (2 × 2) bimatrix form games are used to demonstrate that a noncooperative strategic form game may have a unique pure or mixed strategy Nash equilibrium (Prisoners' Dilemma and Matching Pennies, respectively), may have both pure and mixed strategy Nash equilibria (Battle of the Sexes), or an infinite number of Nash equilibria. Nash's application of the Kakutani fixed point theorem to prove the existence of equilibria is discussed and applied to specific games. Motivated by the possible multiplicity of Nash equilibria in noncooperative strategic form games, the number of equilibria, the construction of games with a unique, prespecified equilibrium, and the calculation of equilibria are considered. The article concludes with a short description of the attempts to refine the Nash equilibrium concept, including perfect and proper equilibria, as well as evolutionary stability.
Network Reliability Performance Metrics
Authors: Antonio Salvatore D. 
Published: February 2011

Abstract
The need to define and use network reliability performance metrics arises from the need to compare different measurement results and to measure network behaviour with a reproducible, unambiguous methodology which is independent from transmission technology and implementation aspects. This introductory article aims at presenting the most important network performance and reliability metrics, and methods for measuring them as defined by the standardization bodies such as the IETF (Internet Engineering Task Force) and ITU‐T.
Newsvendor Models
Authors: Petruzzi Nicholas C. , Dada Maqbool 
Published: February 2011

AbstractThe newsvendor model has a rich and expansive history in operations research and management science. In its essential formulation, the newsvendor model characterizes the following optimization problem: a firm facing random demand for a product that becomes obsolete at the end of a single period must decide how many units of the product to stock in order to maximize expected profit for the period. The celebrated solution to this problem prescribes a supply quantity that equates the expected cost of overstocking to the expected (opportunity) cost of understocking. This classic model, with its intuitively appealing optimal solution, serves as the launch pad for such vast and important literature as stochastic inventory theory, supply chain coordination, and the operations/marketing interface.
N
ewton‐Type Methods
Authors: Murray Walter 
Published: February 2011

Abstract
Newton's method is one of the most famous numerical methods. Its origins, as the name suggests, lies in part with Newton, but the form familiar to us today is due to Simpson of “Simpson's Rule” fame. Originally proposed to find the roots of polynomials it was Simpson who proposed using it for general nonlinear equations and for its use in optimization by finding a root of the gradient. Here, we discuss Newton's method for both of these problems with the focus on the somewhat harder optimization problem. A disadvantage of Newton's method, in its original form, is that it has only local convergence unless the class of functions is severely restricted. Much of the discussion here will be about the many ways in which Newton's method may be modified to achieve global convergence. A key aim of all these methods is that once the iterates come sufficiently close to a solution, the method takes Newton steps.
Nonstationary Input Processes
Authors: Kuhl Michael E. 
Published: February 2011

Abstract
Nonstationary input processes are utilized in simulation to model time‐varying patterns of events. The focus of this article is on modeling and simulating nonstationary arrival processes. In particular, we discuss nonparametric, parametric, and semiparmetric methods for modeling and simulating nonhomogeneous Poisson processes. In addition, we present methods for modeling and simulating nonstationary non‐Poisson arrival processes.
Nurse Scheduling Models
Authors: Bard Jonathan F. 
Published: February 2011

Abstract
The continued interest in nurse scheduling is fueled by both, academic and economic concerns. Most of the issues surrounding the construction of midterm or monthly schedules are present throughout the service industry, so models and methods developed for managing nurses readily carry over to other areas. From a practical point of view, the cost of the nursing staff represents over 50% of the cost of running a health‐care facility so improved scheduling can have a measurable impact on profitability. The goal of this article is to review the parameters that planners must consider when formulating schedules to meet daily staffing requirements in the face of labor agreements, skill requirements, hospital policies, and changing governmental regulations. At the midterm level, models must take into account individual preferences, seniority, the distribution of gaps in coverage, and skill substitution. On a daily basis, critical resources must be tracked and schedules updated to meet changes in demand. Short‐term issues come into play just prior to the beginning of each shift where last‐minute call outs, emergencies, and other unanticipated disruptions imply a need for online control. To find solutions to these problems, various analytic methods have been proposed but few have actually found their way into practice. The article concentrates on the more effective techniques with an eye toward implementation.
Managing Corporate Mobile Voice Expenses: Plan Choice, Pooling Optimization, and Chargeback
Authors: Chiu Samuel S. 
Published: February 2011

Abstract

Mobility communication management spans the spectrum of user choice, device procurement/inventory/replacement, IT security, corporate policy compliance, expense optimization, and billing. Today, there are many vendors providing a subset or a full spectrum of such mobility communication management services to corporate customers, a service collectively (perhaps not quite accurately) known as TEM, telecom expense management. The focus of this article is on mobile voice expense optimization. A mobile voice subscription plan can generally be characterized by three parameters: a monthly fixed charge, a peak minute allowance, and an overage rate when usage exceeds a plan's minute allowance. An (stand‐alone) individual user has to decide which plan to choose: too large a base plan will result in unused wasted minutes, while too small a plan will incur expensive overage charges. Similar to family plans, a corporation has different pooling options. A pooling plan allows subscribers in the same pool to share a common pool of minutes. An overage results when the collective usage exceeds the common pool of minutes. We examine the mathematics behind pooling and how to create the best pooling arrangement minimizing mobile voice expenses. The contribution of this paper first lies in the formulation of the problem, making it tractable. This formulation allows an efficient and effective solution to such a complex combinatory pooling optimization problem, using a column generation technique. We provide case studies to illustrate the potential (and actual savings) for the stand‐alone plan choice decision as well as the collective pooling optimization; typically resulting in 20–30% of annual savings, which translate into tens of millions of dollars for large corporations. A very important, often a stumbling block to implement a pooling solution, aspect of pooling is
chargeback
—how to allocate monthly pooled expenses to individual accounts (which often belong to different units in an organization). We share with you a simple and equitable chargeback scheme, which is well received and readily implemented by corporate clients. An actual case study will be presented as well as some concluding remarks.
Option Pricing: Theory and Numerical Methods
Authors: Babich Volodymyr , Kamrad Bardia 
Published: February 2011

AbstractThe goal of this article is to introduce readers to the fundamental ideas underlying theory and practice of financial derivatives pricing. We begin by defining financial derivatives. Our discussion is focused on stock options, although the same ideas apply to other derivatives. We present commonly used models for the evolution of stock prices: binomial and trinomial trees; and geometric Brownian motion. We discuss shortcomings of these models and suggest alternatives. Using the binomial model for the stock price evolution, we illustrate the main idea of asset pricing theory—no‐arbitrage pricing—and derive the price of a stock option. This formula creates an opportunity to discuss another important idea in asset pricing—risk‐neutral valuation. We introduce the Black–Scholes and Merton model and present the celebrated Black–Scholes and Merton PDE and option pricing formulas. Although some derivatives afford closed form expressions (e.g., Black–Scholes and Merton formulas) for their prices, the vast majority of derivatives must be priced numerically. We discuss advantages and disadvantages of three main numerical methods: lattice models, Monte Carlo simulation, and finite difference methods. The article is concluded with a brief overview the literature that will help readers to continue learning about this fascinating topic.
OR

Models in Freight Railroad Industry
Authors: Nemani Ashish K. , Ahuja Ravindra K. 
Published: February 2011

Abstract

The transportation sector, especially the rail mode, is a very rich source of optimization problems and has been a primary focus of operations researchers. A plethora of articles dedicated to each transportation mode (rail, road, air, and water) can be found in the literature. Ironically, the industries are still using rules of thumb instead of mathematical models for most of the planning and scheduling processes. There are two main reasons for
not
using the operations research (OR) models: (i) the highly complex nature of the problems, and (ii) the huge gap between the academic (theoretical) and industrial (practical) approaches. With the steep growth in computational capabilities, we have started developing innovative algorithms by shifting the focus from finding
optimal‐but‐impractical
solutions to finding
good‐and‐implementable
solutions. We are developing state‐of‐the‐art ideas combining exact approaches such as network flows and mixed integer programming, with heuristics and meta‐heuristics such as the tabu search and the very large‐scale neighborhood (VLSN) search. In this article, we provide an overview of the railroad planning and scheduling problems at the strategic, tactical, and operational levels. We describe the best algorithms successfully implemented at US railroads, which have the potential of saving hundreds of millions of dollars annually.
Single‐Dimensional Search Methods
Authors: Chong Edwin K. P. , Żak Stanislaw H. 
Published: February 2011

Abstract

This article considers the problem of minimizing a real‐valued function defined on the real line (i.e., a single‐dimensional problem). This function is referred to as the
objective function
. The approach is to use an iterative search algorithm, also called a line‐search method. Single‐dimensional search methods are of interest for the following reasons. First, they are special cases of search methods used in multivariable problems. Second, they are used as part of general multivariable algorithms. An iterative algorithm starts with an initial candidate solution and generate a sequence of
iterates
. The iterative algorithm may use only values of the objective function, or perhaps also its first derivative and even its second derivative. This article presents several algorithms: the golden section and Fibonacci methods (which use only objective function values), the bisection and secant methods (which use only derivative values), and Newton's method (which uses both first and second derivatives).
Parametric
LP
Analysis
Authors: Holder Allen 
Published: February 2011

Abstract
Parametric linear programming is the study of how optimal properties depend on data parametrizations. The study is nearly as old as the field of linear programming itself, and it highlights how a problem depends on its data. We present a modern perspective on the classical analysis of the objective value's response to parametrizations in the right‐hand side and/or the cost vector. We also mention a few applications and provide citations for further study.
Partially ObservableMDPs(POMDPS): Introduction and Examples
Authors: Yaylali Emine , Ivy Julie S. 
Published: February 2011

AbstractA partially observable Markov decision process (POMDP) is a generalization of a Markov decision process where the states of the model are not completely observable by the decision maker. Noisy observations provide a belief regarding the underlying state, while the decision maker has some control over the progression of the model through the selection of actions. In this article, we introduce POMDPs and discuss the relationship between Markov models and POMDPs. A general POMDP formulation and a wide range of POMDP applications from the literature are also presented.
Perfect Bayesian Equilibrium and Sequential Equilibrium
Authors: Okada Akira 
Published: February 2011

Abstract
Two equilibrium concepts for an extensive‐form game are reviewed: a (weak) perfect Bayesian equilibrium and a sequential equilibrium. These equilibrium concepts are defined in terms of a pair comprising a behavioral strategy profile and a system of beliefs so that they satisfy sequential rationality and consistency. A (weak) perfect Bayesian equilibrium requires a weak consistency that the Bayes rule should be applied whenever possible. A sequential equilibrium requires a stronger consistency that uses the trembling‐hand approach for a perfect equilibrium.
Mathematical Models for Perishable Inventory Control
Authors: Nahmias Steven 
Published: February 2011

Abstract
This article is intended to provide the reader with the fundamentals underlying the theory of managing perishable inventories. The emphasis is on the mathematical models for perishable inventory control, rather than on the application of these models. Perishable inventories constitute a huge portion of the world economy. These include virtually all foodstuffs and pharmaceuticals and many others. If we view obsolescence as a type of perishability, then most electronic items would be included in this list as well. We hope this article provides the reader with a basic understanding of the issues and mathematics underlying these models, and the tools to pursue further reading on his or her own.
Probability Weighting Functions
Authors: Al‐Nowaihi Ali , Dhami Sanjit 
Published: February 2011

AbstractExpected utility (EU) theory is unable to accommodate the observed nonlinear weighting of probabilities. We outline three stylized facts on nonlinear weighting that a theory of risk must ideally address. These are that people overweight small probabilities and underweight large ones (S1), do not choose stochastically dominated options when such dominance is obvious (S2), and ignore very small probabilities and code extremely large probabilities as one (S3). We then show that the concept of a probability weighting function (PWF) is crucial in addressing S1–S3. A PWF is not, however, in itself, a theory of risk. PWFs need to be embedded within some theory of risk in order to have significant predictive content. The two main alternative theories that are relevant in this regard arerank‐dependent utility(RDU) andcumulative prospect (CP) theory. RDU and CP explain S1, S2 but not S3. We outline the recent proposal of al‐Nowaihi and Dhami forcomposite prospect (CPP) theorythat uses thecomposite Prelec probability weighting function(CPF). CPF is axiomatically founded, is flexible, and, is parsimonious. CPP can explain all three stylized facts S1, S2, and S3.
Push and Pull Production Systems
Authors: Benton W.C. 
Published: February 2011

Abstract
The terms push and pull are used to describe alternative systems for executing the production process in manufacturing organizations. A “push” system is based on forecasted demand that is completed and sent to the next work station or in the case of the final work station is pushed to finished goods inventory. On the other hand, in a “pull” system, the movement of work is based on the requirements of the following work station. Each succeeding workstation pulls (demands) output from the previous workstation as needed. The next work station determines when and how much output is requested. The output from the final workstation is pulled by customer demand or the master production schedule.
The choice between the push and pull systems is based on firm's production–inventory relationship. Firms that have highly repetitive production processes and well‐defined work flows of standardized items require the pull system based on the need for tighter control of inventory and output at the work stations. On the other hand, production processes with long lead times, accurate demand forecasts, a large number of products produced on common production processes, and a diverse customer base tend to use the push systems.
Quasi‐Newton Methods
Authors: Yuan Ya‐Xiang 
Published: February 2011

AbstractQuasi‐Newton methods are a class of important methods for solving unconstrained optimization and for solving nonlinear equations. In this article, a review on quasi‐Newton methods for unconstrained optimization is given. Well‐known quasi‐Newton update formulae are given and theoretical properties of the updates are presented. Convergence results and open questions about quasi‐Newton methods are also given.
Regenerative Processes
Authors: Vlasiou Maria 
Published: February 2011

Abstract
We review the theory of regenerative processes, which are processes that can be intuitively seen as comprising of i.i.d. cycles. Although we focus on the classical definition, we present a more general definition that allows for some form of dependence between two adjacent cycles, and mention two further extensions of the second definition. We mention the connection of regenerative processes to the single‐server queue, to multiserver queues, and more generally to Harris ergodic Markov chains and processes. In the main theorem, we pay some attention to the conditions under which a limiting distribution exists and provide references that should serve as a starting point for the interested reader.
Rendezvous Search Games
Authors: Alpern Steve 
Published: February 2011

AbstractRendezvous search studies the problem faced by a number of people (or animals or robots) who are trying to find each other after becoming separated (perhaps by a storm) or on reaching a large meeting area independently. Formally, it is a common‐interest game where two (or more) unit speed players seek to minimize the time taken to meet. The game begins with a known (sometimes, an unknown) joint distribution of the players in a known search regionQ, which is dark (so the players cannot see each other until they are sufficiently close). Although originally proposed by the author in 1976, these problems did not receive much attention until the 1990s. However, much progress has been made in the last 20 years. These games can be viewed as search game extensions of the spatial coordination problems posed by Schelling in 1960. But where Schelling was concerned with “focal points,” the rendezvous theory typically avoids these by assuming symmetrical search regions.
Renewal Processes With Costs and Rewards
Authors: Vlasiou Maria 
Published: February 2011

Abstract
We review the theory of renewal reward processes, which describes renewal processes that have some cost or reward associated with each cycle. We present a new simplified proof of the renewal reward theorem that mimics the proof of the Elementary Renewal Theorem and avoids the technicalities in the proof that is presented in most textbooks. Moreover, we mention briefly the extension of the theory to partial rewards, where it is assumed that rewards are accrued not only at renewal epochs but also during the renewal cycle. For this case, we present a counterexample which indicates that the standard conditions for the renewal reward theorem are not sufficient; additional regularity assumptions are necessary. We present a few examples to indicate the usefulness of this theory, where we prove the inspection paradox and Little's law through the renewal reward theorem.
Repairable Systems: Renewal and NonRenewal
Authors: Rigdon Steven E. 
Published: February 2011

AbstractRepairable systems are systems that can be restored to an operating condition by some repair operation. Models for repairable system are inherently different from models for nonrepairable systems. For nonrepairable systems, it is reasonable to assume that the lifetimes are independent and identically distributed. Models for the reliability of repairable systems must account for the occurrence of events in time. Often, these event times or interevent times are not independent and not identically distributed. This article presents models for repairable systems that account for these factors.
Risk Averse Models
Authors: Shapiro Alexander 
Published: February 2011

AbstractThis article deals with risk averse stochastic optimization. Various approaches to controlling the risk are discussed in the framework of the portfolio selection problem. An axiomatic approach to constructing coherent risk measures is outlined and it is shown how it can be applied to two‐stage stochastic programming problems. Finally, possible extensions to risk averse multistage stochastic programming are mentioned.
Robust External Risk Measures
Authors: Kou Steven , Peng Xianhua , Heyde Christopher C. 
Published: February 2011

AbstractChoosing a proper external risk measure is of great regulatory importance, as exemplified in the Basel II Accord and its recent revision, which use Value‐at‐Risk (VaR) with scenario analysis as the external risk measure for setting capital requirement. The main motivation of this article is to investigate how to choose a good external risk measure. While many risk measures may be suitable for internal risk management, we argue that risk measures used for external regulation should have robustness with respect to model misspecification (e.g., by incorporating scenario analysis) and small changes in the data (e.g., by using robust statistics). We propose new data‐based risk measures called natural risk statistics that are characterized by a new set of axioms based on comonotonicity from decision theory. Natural risk statistics include VaR with scenario analysis, in particular Basel II risk measures, as special cases; therefore, we provide a theoretical framework to understand and extend the Basel II accord, if needed.