Solving Multi-objective Flexible Job Shop Scheduling with Transportation Constraints using a Micro Artificial Bee Colony Algorithm

被引：0

作者：

Liu, Zhuangcheng ^{[1
]}

Ma, Shuai ^{[1
]}

Shi, Yanjun ^{[1
]}

Teng, Hongfei ^{[1
]}

机构：

[1] Dalian Univ Technol, Sch Mech Engn, Dalian, Peoples R China

来源：

PROCEEDINGS OF THE 2013 IEEE 17TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN (CSCWD) | 2013年

关键词：

flexible job shop scheduling problem; automatic guided vehicle; artificial bee colony; micro genetic algorithm; AUTOMATED GUIDED VEHICLES; GENETIC ALGORITHM; MACHINES;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

We deal with multi-objective Flexible Job Shop Scheduling Problem (FJSSP) with transportation resources constraints herein, where the cost time of loaded and empty Automatic Guided Vehicle (AGV) cannot be neglected. This problem is a NP-hard problem, whose optimization objectives are to minimize the makespan and total workload of machines. We proposed a multi-objective micro artificial bee colony algorithm (MMABC) to tackle this problem. In MMABC, each solution corresponds to a food source, which is encoded to reflect the assignment of AGV tasks, machine operations, and operation sequence; the smaller bee population is divided in two parts: a replaceable bee part and non-replaceable bee part. We also employed the crossover operator to the employed bee for exchanging the good scheduling. Experimental results on larger examples and comparisons with multi-objective micro genetic algorithm showed the effectiveness of the proposed algorithm.

引用

页码：427 / 432

页数：6

共 18 条

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