Showing papers in "International Transactions in Operational Research in 2000"

TL;DR: This article is a survey of heuristics for the Vehicle Routing Problem which contains well-known schemes such as, the savings method, the sweep algorithm and various two-phase approaches and tabu search heuristic which have proved to be the most successful metaheuristic approach.

TL;DR: AHP/DEA ranking does not replace the DEA classification model, rather it furthers the analysis by providing full ranking in the DEA context for all units, efficient and inefficient.

TL;DR: In the context of a concern with a self sustaining system for the management of human resources, those responsible for the Coordination of Human Resources at the Governmental Agency ‘Secretaria de Administracao 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.

TL;DR: This paper illustrates the utility of soft methods, and in particular their combination, with recently published case studies, and proposes an approach to the process of combining methods, including several frameworks and techniques to assist in selecting and linking different methods.

TL;DR: The performance of the well-known tree and Christofides’ heuristics for the traveling salesman problem is investigated in the multicriteria case with respect to the two definitions of approximability.

TL;DR: In this article, a scenario-based multistage stochastic programming model is developed for the management of the Highland Lakes by the Lower Colorado River Authority (LCRA) in Central Texas.

TL;DR: A new version of the algortihm is developed for solving exactly some variants of (un)weighted constrained two-dimensional cutting stock problems with one-dimensional bounded knapsacks and some characteristics of the BOB-library are used.

TL;DR: In this article, a Travelling Salesman Problem with Allocation, Time Window and Precedence Constraints (TSP-ATWPC) is considered, where each ship in the fleet is equipped with a flexible cargo hold that can be partitioned into several smaller holds in a given number of ways.

TL;DR: The MAGISTER (Multicriteria Analysis with GIS for TERritory) model proposes a decision support method to integrate multiple actors of land management based on geographical information systems and multicriteria analysis.

TL;DR: In this article, a neighborhood search algorithm is not practical if the neighborhoods cannot be searched efficiently, thus, a rapid search algorithm was needed to make efficient use of large neighborhoods, which is the case in this paper.

TL;DR: A modeling framework to plan for the supply and demand matching of public hospital beds in Hong Kong for the future years till 2006 is proposed, which includes new services distribution as well as existing services redistribution.

TL;DR: In this article, 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, and the resultant probabilities can be used in a simulation to estimate each player's chance of victory.

TL;DR: A non-linear goal program of the North Sea demersal fisheries is used to develop a genetic algorithm for optimization, and Comparisons between the GA approach and traditional solution methods are made, in order to measure the relative effectiveness.

TL;DR: In this paper, the authors considered the three-machine no-wait flow shop problem with the objective of minimizing total completion time where setup times are considered as separate from processing times and sequence independent.

TL;DR: In this paper, the authors used an extreme point approach to analyze some usual decision criteria for multiple attribute decision-making problems when partial information about the importance of the attributes is available, and obtained results show that the decision criteria to be chosen depend not only on the rationality principles, but also on the structure of the information set.

TL;DR: This paper constructs a new theoretical framework for learning and making improvements based upon learning cycles that allows what is learned in one period to be intelligently applied to the next, improving the rate of learning right as production is occurring.

TL;DR: In this paper, the authors developed a concept of cointegration for these stochastic multifractals and applied it to the exchange rates of three major currencies in the USA.

TL;DR: This paper uses simulated annealing to obtain feasible solutions, and hence, upper bounds on the optimum value, and solves a Lagrangean dual problem using a subgradient optimization method to obtain lower bounds.

TL;DR: In this article, a number of new evolutionary algorithms have been proposed and modifications have been made to several constructive algorithms to cope with non-unique jobs or jobs with multiple demands, and a numerical comparison of these algorithms and real data of a truck assembly line has been presented.

TL;DR: In this paper, a simulation model has been developed to determine the impact of the implementation of environmental programs putting restrictions on fertiliser use and mowing date on dairy farms, and results showing the trade-offs between the economic, environmental and nature protection criteria are given.

TL;DR: The exploitation of recent advances in information and communication technology can be used to remove the communication impediments among spatially dispersed decision makers, efficiently elicit and represent the domain of knowledge, and develop efficient mechanisms to structure and consistently maintain the decision analysis.

TL;DR: The contribution presents an approach to exploit a health insurance databank to evaluate the performance of cardiovascular surgery nation wide.

TL;DR: The problem of identifying regions of congestion in closed queueing networks with state-dependent service rates can be reduced to one of finding them in an isolated subnetwork with suitably modified routing intensities.

TL;DR: The paper describes the methodology and the respective processes of scenario construction and shows that short, intensive, highly interactive workshops are a tool for creating a social basis for policy-in-the-making.

TL;DR: 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 and preliminary experiment results show that repair-action selection made by learned search control knowledge succeeded in improving scheduling quality efficiently.

TL;DR: This work characterize this algorithm by introducing an upper bound on the deviation of the criterion from its optimal value, stated in terms of parameters characterizing the problem, namely number of processors, the length of the longest path, and the total required processing time.

TL;DR: In this article, 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, is discussed.

TL;DR: In this paper, a decision support system (DSS) for automotive product marketing, design and manufacturing in China is presented, which supports decision makers in determining suitable strategies for market entry by analyzing existing competitors' status, growth estimation of each market segment, and competitive market analysis for new vehicle products.

TL;DR: A new parallel breadth first oriented tabu search extension is presented, which can be used to improve existingtabu search procedures for production planning problems and can be installed on nearly every distributed system.

TL;DR: An (M, N)-threshold non-preemptive priority service schedule for a queueing system consisting of two-parallel queues and a multi-server is proposed.