Scheduling multi-objective open shop scheduling using a hybrid immune algorithm

被引：14
|
作者：
Naderi, B. [1 ]
Mousakhani, M. [2 ]
Khalili, M. [3 ]
机构：
[1] Islamic Azad Univ, Qazvin Branch, Young Researchers Club, Qazvin, Iran
[2] Islamic Azad Univ, Sci & Res Branch, Fac Management & Econ, Dept Business Management, Tehran, Iran
[3] Islamic Azad Univ, Karaj Branch, Dept Ind Engn, Karaj, Iran
来源：
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY | 2013年 / 66卷 / 5-8期
关键词：
Open shop scheduling; Multi-objective optimization problems; Metaheuristics; Artificial immune algorithm; Simulated annealing; Performance quality measure; GENETIC ALGORITHMS; COMPLETION-TIME; PARTICLE SWARM; HEURISTICS; VARIANCE;
D O I：
10.1007/s00170-012-4375-x
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Despite their importance, hardly ever have multi-objective open shop problems been the topic of researches. This paper studies the mentioned problem and proposes some novel multi-objective solution methods centered on the idea behind artificial immune and simulated annealing algorithms incorporating with powerful and fast local search engines. First, the algorithms are tuned and then carefully evaluated for their performance by means of multi-objective performance measures and statistical tools. An available ant colony optimization is also brought into the experiment. Among the proposed algorithms, the results show that the variant of enhanced artificial immune algorithm outperforms the others.
引用
收藏
页码：895 / 905
页数：11
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