Showing papers in "Computers & Operations Research in 2002"

TL;DR: This paper presents a method for solving the multi-depot location-routing problem (MDLRP) in which several unrealistic assumptions are relaxed and the setting of parameters throughout the solution procedure for obtaining quick and favorable solutions is suggested.

TL;DR: This work reviews existing work that forms the interface between GIS and Location Science and discusses some of the potential research areas involving both GISand Location Science.

TL;DR: The GP-AHP method developed herein can concurrently tackle the pairwise comparison involving triangular, general concave and concave-convex mixed fuzzy estimates under a group decision-making environment.

TL;DR: This paper seeks to evaluate the performance of genetic algorithms as an alternative procedure for generating optimal or near-optimal solutions for location problems, using a test base of publicly available data sets.

TL;DR: This work considers a generalization of the maximal cover location problem which allows for partial coverage of customers, with the degree of coverage being a non-increasing step function of the distance to the nearest facility.

TL;DR: The simulation results indicate that the proposed scheme is slightly better than the conventional two-stage method with respect to the rate of misclassification, and the real-world data on the basis of Wilk's Lambda and discriminant analysis.

TL;DR: A solution construction method and a tabu search improvement heuristic coupled with the deviation concept found in deterministic annealing are developed to solve the truck and trailer routing problem.

TL;DR: Several new heuristics for solving the one-dimensional bin packing problem are presented, and the most effective algorithm turned out to be one based on running one of the former to provide an initial solution for the latter.

TL;DR: This paper proposes a simulated annealing algorithm to search for a "good" partitioning of the police jurisdiction and employs a variant of the well-known PCAM model to optimally assign the patrol cars and assess the "goodness" of a particular district design with respect to some prescribed performance measures.

TL;DR: An attempt has been made to develop an efficient approach based on genetic algorithm for solving bilevel programming problem by providing some theorems that makes the algorithm more efficient than other techniques.

TL;DR: This paper considers the problem of scheduling jobs with non-identical capacity requirements, on a single-batch processing machine of a given capacity, to minimize the makespan and provides an exact method for the makepan criterion.

TL;DR: Two types of fuzzy optimisation models are discussed in this paper, which consider not only the overall customer satisfaction, but also the enterprise satisfaction with the costs committed to the product.

TL;DR: This work adapts a dynamic programming algorithm from the literature to determine whether a due-date feasible batching exists for a given job sequence, and combines this algorithm with a random keys encoding scheme to develop a genetic algorithm for this problem.

TL;DR: This paper significantly extends traditional facility location models by introducing several logistical cost components such as holding, ordering, and transportation costs in a multi-commodity, multilocation framework.

TL;DR: This paper investigates the lot size, reorder point inventory model involving variable lead time with partial backorders, where the production process is imperfect, and applies the minimax distribution-free procedure to solve the problem.

TL;DR: Using the reliability estimation methods of the ANN, the upperbound and backtracking, optimal network design by simulated annealing is considered and results show that the ANN regularly produces superior network designs at a reasonable computational cost.

TL;DR: A scenario-based approach for capturing the evolution of demand and a stochastic programming model for determining technology choices and capacity plans are developed, which is likely to be large and may not be easy to solve with standard software packages.

TL;DR: The optimal policy is derived for an inventory model that allows stock disposal, and is shown to be the solution of a dynamic programming backward recursion, and a method is given to search for the optimal order level around the myopic order level.

TL;DR: A greedy randomised adaptive search procedure (GRASP) which is very fast and obtains good results for both constrained and unconstrained problems, and a more complex tabu search algorithm that obtains high quality results in moderate computing times.

TL;DR: This paper considers a generalization of the permutation flow shop problem that combines the scheduling function with the planning stage, and considers a nonregular optimization criterion based on due dates which are not a priori given but can be fixed by a decision-maker.

TL;DR: HubLocator is a new branch-and-bound procedure for the uncapacitated multiple allocation hub location problem which considers an aggregated model formulation enabling us to significantly tighten the lower bounds.

TL;DR: In this study a functional representation of the tabu list size is presented and a softer aspiration criterion is put forward.

TL;DR: The steady state queue size distribution at different points in times, as well as the steady state distributions of busy period and unfinished work (backlog) of this model are derived.

TL;DR: This research develops a model and a solution algorithm to help carriers simultaneously solve for better fleet routes and appropriate timetables and the results of a case study show the model's good performance.

TL;DR: This work examines the profitability of job selection decisions over a number of periods when current orders exceed capacity with the objective of maximizing profit, and finds one heuristic that produces near-optimal results for small problems, is tractable for larger problems, and requires the same information as the dynamic program.

TL;DR: Experimental studies show that EP can provide a simple yet more effective alternative to GAs in solving cutting stock problems with and without contiguity.

TL;DR: A new iterative method is presented that combines the simulated annealing method and the ranking and selection procedures for solving discrete stochastic optimization problems and is guaranteed to converge almost surely to a global optimal solution.

TL;DR: A longest path type algorithm over an acyclic graph is devised in order to maximize the objective function, in which it was necessary to approximately determine the catchment area for each station.

TL;DR: An appropriate time-dependent partial backlogging rate is defined and the opportunity cost due to lost sales should be considered since some customers would not like to wait for backlogging during the shortage periods.

TL;DR: This paper studies how the level of retail-market demand uncertainty will affect the decisions (w, r, Q, p), the expected manufacturer's profit and the expected retailer's profit.