Showing papers in "Computers & Operations Research in 1997"

TL;DR: This chapter presents the basic schemes of VNS and some of its extensions, and presents five families of applications in which VNS has proven to be very successful.

TL;DR: Computational results show that the genetic algorithm heuristic is able to find optimal and near optimal solutions that are on average less than 0.01 % from optimality.

TL;DR: This article deals with the problem of determining the retailer's optimal price and lot size simultaneously when the supplier permits delay in payments for an order of a product whose demand rate is represented by a constant price elasticity function.

TL;DR: In this article, an exact hybrid solution procedure, called BISON, is proposed for solving BPP-1, which combines the well-known meta-strategy tabu search and a branch and bound procedure based on known and new bound arguments and a new branching scheme.

TL;DR: This article addresses the problem of simultaneous scheduling of machines and a number of identical automated guided vehicles (AGVs) in a flexible manufacturing system (FMS) so as to minimize the makespan using a genetic algorithm (GA) proposed.

TL;DR: In this article, both lead time and the order quantity are considered as the decision variables of a mixture inventory model and an algorithm procedure is developed to find the optimal order quantity and optimal lead time.

TL;DR: A tabu search based adaptive memory procedure of instances indicate that the method produces very good solutions within reasonable computing times.

TL;DR: A measure of the saliency of the input variables that is based upon the connection weights of the neural network is examined, and it is found that the method works quite well in identifying significant variables under a variety of experimental conditions, including neural network architectures and data configurations.

TL;DR: In this paper, a traveling salesman approach was proposed for solving Mixed Rural Postman Problems and Stacker Crane Problems to optimality on low-density graphs with few edges, and it was shown that the approach works well on low density graphs containing few edges.

TL;DR: Two pseudo-polynomial time algorithms are provided which show that the problem is solvable in polynomial time if either the job processing times or the job weights for the lateness penalty are equal and a fully polynometric time approximation scheme which always generates a solution within a specified percentage of the optimal.

TL;DR: It is suggested that individually optimized results can be used to build group consensus and rather than using ordinal rankings for aggregation which do not consider preference strength, a procedure that takes account of individual DMs' preference strength is suggested.

TL;DR: It is concluded that Genetic Algorithms, Simulated Annealing and the Continuous Simulating Annealing which are non-gradient based optimization techniques are reliable and accurate for solving machining optimization problems and offer certain advantages over gradient based methods.

TL;DR: A comprehensive analysis of an M/G/1 queue with repeated attempts in which the server operates under a general exhaustive service vacation policy is developed, including ergodicity, limiting behaviour, stochastic decomposition and optimal control.

TL;DR: An improved version of this algorithm is proposed by introducing one-dimensional bounded knapsacks in the original algorithm, and is compared to the standard version of Viswanathan and Bagchi on some small and medium instances.

TL;DR: A Monte Carlo simulation of a decision-maker who picks random judgments out of a distribution centered at his or her true judgment suggests that, if the final consistency ratio is less than 0.10, additional artificial manipulation to lower the consistency ratio will improve the reliability of the analysis.

TL;DR: A computational procedure is developed that efficiently evaluates the mean flow-times for large number of customers that need to be scheduled and is integrated with a nonlinear program that determines the optimal customer arrival times.

TL;DR: It is proposed that inputs which are not substitutes for each other be assessed separately and only with respect to outputs which consume them or to which they are otherwise related, and input-specific efficiency ratings are derived giving a profile for each DMU.

TL;DR: The results show that MDD rule outperforms other existing rules by a large margin and can be incorporated into other rules to improve their performances.

TL;DR: This article uses tabu search to solve the restricted, common-due-date, early/tardy machine scheduling problem generalised earliness and tardiness penalties and results show that a search which uses an early/Tardy solution space with a neighbourhood scheme which eliminates infeasible areas of the solution space is the most efficient and effective solution method.

TL;DR: The article examines the sequential heuristic procedure for optimisation of roll cutting in the clothing industry through a combination of approximations and heuristics and found an item-oriented solution.

TL;DR: An alternative method that utilizes a penalty cost to solve a FGP problem with preemptive structure is proposed, which has transformed an FGP into a simpler form which can be solved with 1 iteration.

TL;DR: The results indicate that a simple level order release strategy in conjunction with a due date based scheduling rule provides an efficient means of releasing and scheduling work in this environment.

TL;DR: An experiment that examines the effects of the anchoring and adjustment bias in two different interactive MCDM solution methods suggests that subjects are anchored by the starting point in the Zionts and Wallenius method, but the effect of anchoring is not significant in the free search method.

TL;DR: A model to determine the required number and position of sidings on a single track rail corridor, with allowance of variable train velocities and non-uniform departure times is put forward.

TL;DR: This article considers the lot-sizing problem in multi-stage production settings with capacity-constrained resources and a heuristic method build upon a formulation of the problem in terms of echelon stock is developed.

TL;DR: This article shows how fuzzy linear programming may be used to solve production scheduling problem in coal industry by using production cost estimates from independent coal mines in the states of Virginia, Illinois and Pennsylvania.

TL;DR: This article develops an inexact approach to solve this type of model of quadratic programming problems with fuzzy objective and resource constraints by using a Genetic Algorithm with mutation along the weighted gradient direction to find a family of solutions with acceptable membership degrees.

TL;DR: This paper compares the performance of two codes for convex 0–1 mixed integer nonlinear programs on a number of test problems and demonstrates that both approaches are generally capable of solving the test problems.

TL;DR: An extensive review of relevant work previously published in the area of graph drawing is presented and a tabu search implementation is presented that seeks high-quality drawings by means of an intensification phase that finds a local optimum according to an insertion mechanism and two levels of diversification.

TL;DR: A unified model of the problem is presented that includes the number, locations, and capacities of service facilities as variables to be determined in the model and incorporates in the total cost to be minimized the user waiting time (queueing) cost.