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Tabu search methods for a single machine scheduling problem
Authors:Manuel Laguna  J. Wesley Barnes  Fred W. Glover
Affiliation:(1) Graduate Program in Operations Research, Department of Mechanical Engineering, The University of Texas at Austin, USA;(2) US West Chair in Systems Science, Center for Applied Artificial Intelligence, Graduate School of Business, University of Colorado at Boulder, USA
Abstract:In this paper we discuss the use of three local search strategies within a tabu search (TS) method for the approximate solution of a single machine scheduling problem. The problem consists of minimizing the sum of the set-up costs and linear delay penalties whenN jobs, arriving at time zero, are to be scheduled for sequential processing on a continuously available machine. Following a review of a previous study of this problem, we first consider a TS method that uses the common approach of making a succession of pairwise job exchanges, or swaps, to move from one trial solution to another. Next, we consider the use of insert moves to define the local neighborhood of each trial solution. These moves consist of transferring a single job from one position to another in the schedule. Finally, we construct a TS method (TS-hybrid) that employs both swap and insert moves. Experiments with benchmark problems of up to 60 jobs illustrate that there is an advantage in using more than one strategy to move from one trial solution to another within a TS method.This work was begun during the author's summer internship at the Advanced Knowledge Systems Group of US West Advanced Technologies.
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