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Tabu search methods for a single machine scheduling problem

Tabu search methods for a single machine scheduling problem 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Intelligent Manufacturing Springer Journals

Tabu search methods for a single machine scheduling problem

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References (16)

Publisher
Springer Journals
Copyright
Copyright
Subject
Business and Management; Production; Manufacturing, Machines, Tools, Processes; Control, Robotics, Mechatronics
ISSN
0956-5515
eISSN
1572-8145
DOI
10.1007/BF01471219
Publisher site
See Article on Publisher Site

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.

Journal

Journal of Intelligent ManufacturingSpringer Journals

Published: Mar 29, 2005

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