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Received:January 05, 2011 Revised:February 01, 2011
Received:January 05, 2011 Revised:February 01, 2011
中文摘要: 在结合遗传算法和量子理论的基础上,提出了一种改进的量子遗传算法(IQGA)求解模糊交货期多机并行调度问题.采用量子比特相位比较法更新量子位,以加快搜索的速度和效率;采用求反解码操作,以扩大种群规模.通过仿真验证,改进的量子遗传算法在求解模糊交货期多机并行调度问题时有较好的寻优能力.
Abstract:Based on the combination of evolutionary theory and quantum theory, this paper proposes an improved quantum genetic algorithm (IQGA) to solve fuzzy due date scheduling problem on parallel machines. It updates the quantum gates with quantum phase comparison method to speed up the search for efficiency; using inverted decoding operation to expand the population size. The simulation results show that the proposed quantum genetic algorithm for fuzzy Due Date on Parallel Machines with better search capabilities.
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基金项目:浙江省重大科技专项课题(2009C11024)
引用文本：
吴灵芝,黄德才.解模糊交货期多机并行调度问题的改进量子遗传算法.计算机系统应用,2011,20(9):73-77
WU Ling-Zhi,HUANG De-Cai.Improved Quantum Genetic Algorithm for Fuzzy Due Date for Parallel Machines.COMPUTER SYSTEMS APPLICATIONS,2011,20(9):73-77
吴灵芝,黄德才.解模糊交货期多机并行调度问题的改进量子遗传算法.计算机系统应用,2011,20(9):73-77
WU Ling-Zhi,HUANG De-Cai.Improved Quantum Genetic Algorithm for Fuzzy Due Date for Parallel Machines.COMPUTER SYSTEMS APPLICATIONS,2011,20(9):73-77
