A hybrid chaotic quantum evolutionary algorithm for resource combinatorial optimization in manufacturing grid system

被引：0
|
作者：
Haijun Zhang
Yefa Hu
机构：
[1] Wuhan University of Technology,School of Mechanical and Electronic Engineering
[2] Hubei Digital Manufacturing Key Laboratory,undefined
来源：
The International Journal of Advanced Manufacturing Technology | 2011年 / 52卷
关键词：
Manufacturing grid; Quantum evolutionary algorithm; Chaotic search; Combinatorial optimization; Resource encoding;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Resource composition in manufacturing grid (MGrid) system is one of the recent critical issues of MGrid researches. Especially, resource combinatorial optimization (RCO) becomes more challenging when multiple optimal criteria are considered in MGrid system. Based on the quantum evolution theory, we propose a hybrid chaotic quantum evolutionary algorithm (CQEA) for RCO problems. We also propose a novel resource encoding method for CQEA, which is dynamic and flexible. The experimental results show that the proposed CQEA is effective, efficient, and scalable for the RCO problem in MGrid system.
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页码：821 / 831
页数：10
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