摘要
采用博弈理论,建立了一种基于非合作博弈的作业车间任务调度模型.在该任务调度模型中,将源于不同客户的制造任务映射为非合作博弈模型中的局中人,并将与制造任务包含的工序集所对应的可选加工设备映射为可行方案集,使各制造任务的加工完成时间和成本组合形成的多目标综合指标映射为收益函数,从而将对任务调度模型的求解转换为寻求非合作博弈模型的Nash均衡点.通过设计的爬山搜索混合自适应遗传算法、自适应交叉和变异算子,实现了对该任务调度非合作博弈模型的Nash均衡点的有效求解,同时算例仿真结果也验证了所提出的调度方法的正确性.
To meet the competition requirements of jobs submitted by different customers in job-shop scheduling,taking the maximal profit of each job as the scheduling objective,a non-cooperation game model is proposed.In this job-shop scheduling game model,the players correspond to the jobs submitted by related customers,the strategies of each job correspond to the alternative machines related to operations of this job,and the payoff of each job is defined as the weighted composite of finishing time and cost.Therefore,obtaining the optimal scheduling results is determined by the Nash equilibrium point of this non-cooperation game.To find the Nash equilibrium point efficiently,a hybrid adaptive genetic algorithm based on hill-climbing method is designed as well as the adaptive crossover operator and mutation operator.A numerical case study demonstrates the validity of the job-shop scheduling strategy.
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2010年第5期35-39,70,共6页
Journal of Xi'an Jiaotong University
基金
国家自然科学基金资助项目(50605050)
国家"863计划"资助项目(2007AA002Z108)
西安交通大学机械制造系统工程国家重点实验室开放基金资助项目
