协同震荡搜索混沌粒子群求解资源受限项目调度问题

doi:10.11772/j.issn.1001-9081.2014.06.1798

计算机应用 ›› 2014, Vol. 34 ›› Issue (6): 1798-1802.DOI: 10.11772/j.issn.1001-9081.2014.06.1798

协同震荡搜索混沌粒子群求解资源受限项目调度问题

戴月明,汤继涛,纪志成

江南大学物联网工程学院,江苏无锡 214122

收稿日期:2013-10-21 修回日期:2013-12-02 发布日期:2014-07-02 出版日期:2014-06-01
通讯作者: 汤继涛
作者简介:戴月明(1964-),男,江苏常熟人,副教授,主要研究方向:人工智能、模式识别、数据挖掘;
汤继涛(1987-),男,江苏邳州人,硕士研究生,主要研究方向:人工智能、模式识别;
纪志成(1959-),男,浙江宁波人,教授,博士,主要研究方向:复杂非线性控制、智能控制。
基金资助:
国家863计划项目;江苏省产学研联合创新基金资助项目

Cooperative shock search particle swarm optimization with chaos for resource-constrained project scheduling problems

DAI Yueming,TANG Jitao,JI Zhicheng

School of Internet of Things Engineering, Jiangnan University, Wuxi Jiangsu 214122, China

Received:2013-10-21 Revised:2013-12-02 Online:2014-07-02 Published:2014-06-01
Contact: TANG Jitao

摘要/Abstract

摘要：

针对求解资源受限项目调度问题(RCPSP),提出了协同震荡搜索混沌粒子群(CSCPSO)算法。算法围绕种群粒子吸引子建立双向协同震荡搜索机制,该机制一方面使粒子向吸引子收敛,另一方面使粒子震荡调整自身与吸引子相邻维度大小关系不一致的维度,提升算法的搜索精度和种群的多样性。项目调度采用基于粒子的拓扑排序和串行项目进度生成机制,保证项目调度解决方案满足资源约束和紧前约束。采用具体算例对算法进行检验,结果表明该算法在求解RCPSP的精度和稳定性方面表现更优。

Abstract:

For Resource-Constrained Project Scheduling Problems (RCPSP), the Cooperative Shock search Particle Swarm Optimization with Chaos (CSCPSO) was proposed. On the basis of particle attractor, a bidirectional cooperation shock search mechanism was established in the algorithm to enhance the search accuracy and diversity of population. The particles converged to particle attractor, meanwhile they adjusted the dimensions whose adjacent relationship were inconsistent with attractor's by shock search in the mechanism. Combined with topological sorting based on particles and serial schedule generation scheme, the gotten scheduling scheme could meet the project schedule constraints of resource and precedence relations. The tests on specific examples show that the proposed algorithm can get higher accuracy and better stability for RCPSP.

中图分类号:

TP391

戴月明汤继涛纪志成. 协同震荡搜索混沌粒子群求解资源受限项目调度问题[J]. 计算机应用, 2014, 34(6): 1798-1802.

DAI Yueming TANG Jitao JI Zhicheng. Cooperative shock search particle swarm optimization with chaos for resource-constrained project scheduling problems[J]. Journal of Computer Applications, 2014, 34(6): 1798-1802.

参考文献

[1]VALLS V, BALLESTIN F, QUINTANILLA S. Justification and RCPSP: a technique that pays [J]. European Journal of Operational Research, 2005, 165(2): 375-386.
[2]KOLISCH R, HARTMANN S. Experimental investigation of heuristics for resource-constrained project scheduling: an update [J]. European Journal of Operational Research, 2006, 174(1): 23-37.
[3]WANG H, LIN D, LI M. Genetic algorithm for multi-objective resource-constrained project scheduling problem [J]. Computer Engineering and Applications, 2008, 44(7): 1-4. (王宏,林丹,李敏强.一种求解多目标资源受限项目调度的遗传算法[J].计算机工程与应用,2008,44(7):1-4.)
[4]MERKLE D, MIDDENDORF M, SCHMECK H. Ant colony optimization for resource-constrained project scheduling [J]. IEEE Transactions on Evolutionary Computation, 2002, 6(4): 333-346.
[5]YU X, ZHAN D, NIE L. Genetic simulated annealing algorithm for resource-constrained project scheduling problem [J]. Computer Engineering and Applications, 2009, 45(24): 17-20. (喻小光,战德臣,聂兰顺.应用遗传模拟退火算法实现资源受限项目调度[J].计算机工程与应用,2009,45(24):17-20.)
[6]WANG W, ZHAO G. Particle swarm optimization for resource-constrained project scheduling problem[J]. Journal of Harbin Institute of Technology, 2007, 39(4): 669-672. (王巍,赵国杰.粒子群优化在资源受限工程调度问题中的应用[J].哈尔滨工业大学学报,2007,39(4):669-672.)
[7]KENNEDY J, EBERHART R C. Particle swarm optimization [C]// Proceedings of the 1995 IEEE International Conference on Neural Networks. Piscataway: IEEE Press, 1995: 1942-1948.
[8]CAPONETTO R, FORTUNA L, FAZZINO S. Sequences to improve the performance of evolutionary algorithms [J]. IEEE Transactions on Evolutionary Computation, 2003, 7(3): 289-304.
[9]CLERC M, KENNEDY J. The particle swarm: explosion, stability, and convergence in a multi-dimensional complex space [J]. IEEE Transactions on Evolutionary Computation, 2002, 6(1):58-73.
[10]TANG J, DAI Y. Regional shock search embedded particle swarm optimization algorithm [J]. Computer Engineering and Applications, 2013, 49(21): 33-36. (汤继涛,戴月明.内嵌区域震荡搜索的粒子群优化算法[J].计算机工程与应用,2013,49(21):33-36.)
[11]ZHANG K, ZHAO G, JIANG J. Particle swarm optimization method for resource-constrained project scheduling problem [C]// ICEMI 2009: Proceedings of the Ninth International Conference on Electronic Measurement & Instruments. Piscataway: IEEE Press, 2009: 792-796.
[12]XIE Y, YE C, CHEN J, et al. Resource-constrained project scheduling based on chaos particle swarm optimization [J]. Industrial Engineering Journal, 2012, 15(3): 57-61.(谢阳,叶春明,陈君兰,等.基于混沌粒子群的资源受限项目调度问题[J].工业工程,2012,15(3):57-61.)
[13]NI L, DUAN C, ZHONG H. Multi-project scheduling based on simulated harmonic oscillator algorithm [J]. , 2011, 31(9): 2559-2562.(倪霖,段超,钟辉.基于模拟谐振子算法的多项目调度[J].计算机应用,2011,31(9):2559-2562.)

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协同震荡搜索混沌粒子群求解资源受限项目调度问题

Cooperative shock search particle swarm optimization with chaos for resource-constrained project scheduling problems

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