Particle swarm optimization algorithm for single machine total weighted tardiness problem

被引:124
作者
Tasgetiren, MF [1 ]
Sevkli, M [1 ]
Liang, YC [1 ]
Gencyilmaz, G [1 ]
机构
[1] Fatih Univ, Dept Management, TR-34500 Istanbul, Turkey
来源
CEC2004: PROCEEDINGS OF THE 2004 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1 AND 2 | 2004年
关键词
D O I
10.1109/CEC.2004.1331062
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. present a particle swarm optimization algorithm to solve the single machine total weighted tardiness problem. A heuristic rule, the Smallest Position Value (SPV) rule, is developed to enable the continuous particle swarm optimization algorithm to be applied to all classes of sequencing problems, which are NP-hard in the literature. A simple but very efficient local search method is embedded in the particle swarm optimization algorithm. The computational results show that the particle swarm algorithm is able to find the optimal and best-known solutions on all instances of widely used benchmarks from the OR libary.
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页码:1412 / 1419
页数:8
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