化工学报 ›› 2012, Vol. 63 ›› Issue (9): 2972-2979.DOI: 10.3969/j.issn.0438-1157.2012.09.048

• 过程系统工程 • 上一篇    下一篇

带修复操作整型编码遗传算法求解大规模机组组合问题

张伟1, 赵进慧2, 王宁1   

  1. 1. 浙江大学智能系统与控制研究所, 浙江 杭州 310027;
    2. 东北大学流程工业综合自动化国家重点实验室, 辽宁 沈阳 110819
  • 收稿日期:2012-06-16 修回日期:2012-06-24 出版日期:2012-09-05 发布日期:2012-09-05
  • 通讯作者: 赵进慧
  • 作者简介:张伟(1982-),男,博士研究生。
  • 基金资助:

    国家博士后基金项目(2011M500567)。

Integer-coded genetic algorithm with novel repairing mechanism for large scale unit-commitment problem

ZHANG Wei1, ZHAO Jinhui2, WANG Ning1   

  1. 1. Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027, Zhejiang, China;
    2. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, Liaoning, China
  • Received:2012-06-16 Revised:2012-06-24 Online:2012-09-05 Published:2012-09-05
  • Supported by:

    supported by China Postdoctoral Science Foundation(2011M500567).

摘要: 针对发电机组组合调度问题,提出了一种带修复操作的整型编码遗传算法(r-ICGA)。算法采用整数串的编码方式,有效减小了染色体的长度。同时引入一组新的修复操作来处理约束,将进化过程中产生的新个体修复成为可行个体。与罚函数约束处理方法相比,所提算法不引入惩罚项,避免了针对不可行解的经济负载分配子问题求解,节省了大量计算时间。将所提方法应用于六种不同规模的机组组合问题,仿真结果表明算法的搜索效率更高,求得的调度结果更好。随机组规模增大,算法所需执行时间近似线性地平缓增长,表明r-ICGA算法比其他方法更适合于求解大规模机组组合调度问题。

关键词: 生产调度, 机组组合, 遗传算法, 整型编码, 修复操作

Abstract: An approach to solving large scale unit-commitment(UC)problem based on integer-coded genetic algorithm(GA)with novel repairing mechanism(r-ICGA)is presented.The GA chromosome consists of integer string,which has shorter length than binary string.Using the proposed repairing mechanism,new chromosomes produced in evolution process are repaired to comply with all constraints.As the alternative to penalty function method,the repairing mechanism turns solutions to feasible ones,and avoid coping with economic load dispatch(ELD)sub-problem for infeasible solutions.The algorithm is tested and validated in 6 cases with different scale up to 100 units.The solutions obtained by r-ICGA have lower operating costs,and the algorithm has approximate linear execution time versus unit number.These simulation results indicate that r-ICGA is more appropriate to large scale unit-commitment problem.

Key words: process scheduling, unit-commitment, genetic algorithm, integer-coded, repairing mechanism

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