Case study for the scheduling problem in the tobacco industry

被引：0
|
作者：
Zhang, Haijun [1 ]
Yan, Qiong [2 ]
机构：
[1] School of Mechatronics Engineering, Zhengzhou University of Aeronautics, Zhengzhou,450046, China
[2] School of Management Engineering, Zhengzhou University of Aeronautics, Zhengzhou,450046, China
来源：
Paper Asia | 2018年 / 2018卷 / COMPENDIUM 5期
关键词：
Simulated annealing - Genetic algorithms - Scheduling;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, the scheduling problem of cut tobacco (SPCT) in the tobacco industry is considered with multi-objectives and multi-resource constraints. To solve such a hard SPCT, this paper proposes a hybrid heuristic, namely GASA, based on genetic algorithm (GA) and simulated annealing (SA) algorithm. This paper first reviews the literature on the scheduling problems using meta-heuristics. For the comparative evaluation, a real case data is extracted from a tobacco plant. The proposed GASA is compared with GA and SA and the comparative results are presented. The proposed GASA is found to perform well for the SPCT. © 2018, SHPMedia Sdn Bhd. All rights reserved.
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页码：82 / 85
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