Minimizing Total Tardiness on Identical Parallel Machines Using VNS with Learning Memory

被引：0

作者：

Lalla-Ruiz, Eduardo ^{[1
]}

Voss, Stefan ^{[2
]}

机构：

[1] Univ La Laguna, Dept Comp & Syst Engn, San Cristobal De Laguna, Spain

[2] Univ Hamburg, Inst Informat Syst, Hamburg, Germany

来源：

LEARNING AND INTELLIGENT OPTIMIZATION, LION 9 | 2015年 / 8994卷

关键词：

ALGORITHM;

D O I：

10.1007/978-3-319-19084-6_10

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Minimizing total tardiness on identical parallel machines is an NP-hard parallel machine scheduling problem that has received much attention in literature due to its direct application to real-world applications. For solving this problem, we present a variable neighbourhood search that incorporates a learning mechanism for guiding the search. Computational results comparing with the best approaches for this problem reveals that our algorithm is a suitable alternative to efficiently solve this problem.

引用

页码：119 / 124

页数：6

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