Multi-objective flexible job shop schedule based on ant colony algorithm
In this paper,an improved ant colony algorithm is proposed to solve solving multi-objective flexible shop scheduling problem.Limitations of the traditional ant colony algorithm weighting coefficient method will result in a greater impact on the results because the determination of the weighting factor has greater subjective factors.Proposed algorithm adds a set of BPs to save all the Pareto set ant appear after iteration,the algorithm improves the search capabilities of the ant colony.The convergence speed is improved on ameliorating the pheromone update rule based on the global optimal experience to guide the optimization way.Thus,multi-objective Flexible Job Shop Scheduling Problems Pareto optimal solution was conducted.Finally,the proposed theory in this paper is proved to solve the multi-objective flexible job shop scheduling optimization problems by examples.
Multi-objective optimization Flexible job shop scheduling problems Ant colony algorithm Pareto optimal solution
Jiang Xuesong Tao Qiaoyun
Qilu University Of Technology Ji Nan,China
国际会议
贵阳
英文
70-73
2015-08-18（万方平台首次上网日期，不代表论文的发表时间）