| 应用新型量子粒子群优化算法求解PFSP问题 |
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| 引用本文： | 叶春明,陈子皓,寇明顺.应用新型量子粒子群优化算法求解PFSP问题[J].技术与创新管理,2012(2):162-165. |
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| 作者姓名： | 叶春明 陈子皓 寇明顺 |
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| 作者单位： | 上海理工大学管理学院 |
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| 基金项目： | 教育部人文社会科学规划基金项目(10YJA630187);高等学校博士点基金(20093120110008);上海市重点学科建设项目(S30504);上海市研究生创新基金项目(JWCXSL1022) |
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| 摘 要： | 为了提高粒子群算法在求解调度问题时的搜索能力和优化效率以及避免早熟收敛。通过采用了一种新颖的量子粒子群算法,用量子位的概率幅对粒子位置编码,用量子旋转门实现粒子移动,完成粒子搜索;并采用量子非门来实现变异,从而提高种群多样性。由于每个量子都有两个概率幅,因此每个粒子实际占据两个粒子位置,所以在粒子数目相等的情况下,能加速粒子的搜索进程。仿真实验结果表明,在求解置换流水线生产调度问题时优于基本粒子群算法。
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| 关 键 词： | 智能群优化算法 粒子群优化算法 量子粒子群算法 置换流水线调度问题 |
Using New QPSO Algorithm to Solve Permutation Flow-shop Scheduling Problem |
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| YE Chun-ming,CHEN Zi-hao,KOU Ming-shun.Using New QPSO Algorithm to Solve Permutation Flow-shop Scheduling Problem[J].Technology and Innovation Management,2012(2):162-165. |
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| Authors: | YE Chun-ming CHEN Zi-hao KOU Ming-shun |
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| Institution: | (College of Management,University of Shanghai for Science and Technology,Shanghai 200093,China) |
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| Abstract: | In order to improve the speed and efficiency of PSO and to avoid premature convergence and being easy to run into local optima,the new quantum particle swarms optimization algorithm is proposed to be applied to permutation flow-shop scheduling problem.This algorithm adopt quantum rotation gate to update the position of particle,and quantum controlled-non gate to achieve the particle variation.This can help to improve population diversity.As a result,each quantum has two probability amplitudes,and any particle has two positions actually.So when the numbers of particles are the same,the new QPSO can speed up the search process.According to the simulation results,the new QPSO algorithm in solving FPSP is better than basic PSO algorithm. |
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| Keywords: | Swarm Intelligence Algorithm Particle Swarm Optimization(PSO) Algorithm Quantum Particle Swarms Optimization(QPSO) Algorithm Permutation Flow-Shop scheduling problem(PFSP) |
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