TABU SEARCH METHODS FOR A SINGLE-MACHINE SCHEDULING PROBLEM

被引:78
|
作者
LAGUNA, M
BARNES, JW
GLOVER, FW
机构
[1] UNIV TEXAS, DEPT MECH ENGN, GRAD PROGRAM OPERAT RES, AUSTIN, TX 78712 USA
[2] UNIV COLORADO, GRAD SCH BUSINESS, CTR APPL ARTIFICIAL INTELLIGENCE, US W CHAIR SYST SCI, BOULDER, CO 80309 USA
关键词
D O I
10.1007/BF01471219
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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 when N 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.
引用
收藏
页码:63 / 74
页数:12
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