Adaptive temperature schedule determined by genetic algorithm for parallel simulated annealing

被引：3

作者：

Miki, M ^{[1
]}

Hiroyasu, T ^{[1
]}

Wako, J ^{[1
]}

Yoshida, T ^{[1
]}

机构：

[1] Doshisha Univ, Knowledge Engn Dept, Kyoto 6100394, Japan

来源：

CEC: 2003 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-4, PROCEEDINGS | 2003年

关键词：

simulated annealing; genetic algorithm; adaptive temperature; traveling; salesman problems; jobshop scheduling problems;

D O I：

10.1109/CEC.2003.1299611

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Simulated annealing (SA) is an effective general heuristic method for solving many combinatorial optimization problems. This paper deals with two problems in SA. One is the long computational time of the numerical annealings, and the solution to it is the parallel processing of SA. The other one is the determination of the appropriate temperature schedule in SA, and the solution to it is the introduction of an adaptive mechanism for changing the temperature. The multiple SA processes are performed in multiple processors, and the temperatures in the SA processes are determined by a genetic algorithms. The proposed method is applied to solve many TSPs (Traveling Salesman Problems) and JSPs (Jobshop, Scheduling Problems), and it is found that the method is very useful and effective.

引用

页码：459 / 466

页数：8

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