基于混沌量子算法和MAGTD的多目标FJSP求解策略

针对多目标环境下柔性作业车间的调度问题,以最小化最大完工时间和惩罚值为目标,建立调度问题的数学模型,提出了基于混沌理论的量子粒子群算法。针对实际生产交货期不确定的特点,在量子粒子群算法基础上,提出引入混沌机制建立初始群的方法;利用混沌机制的遍历性,提出混沌局部优化策略;为获取最优调度方案提出了引入多指标加权灰靶选择策略。通过典型基准算例和对比测试,验证了所提出的算法获得最满意调度方案的可行性和求解多目标柔性作业车间调度问题的有效性。

Study on Multi-objective Flexible Job Shop Scheduling Basedon Chaos Quantum Optimization and MAGTD

In order to solve the flexible job-shop scheduling(FJSP problem in the multi objective environment, the simulation model is established aiming at minimizing the makespan and penalty, and an improved chaos quantum particle swarm optimization(IQPSO)algorithm is proposed. On the basis of the characteristics of the production delivery time in actual production, we introduce the method of initializing population with chaos mechanism. To update the quantum individual, we propose a novel method to improve the quantum rotating angle. The chaos local optimization strategy using the ergodicity of chaos mechanism is proposed. The multi-attribute decision model based on weighted grey target strategy is introduced to select the most satisfied schedule scheme. The feasibility of the proposed algorithm and the validity of solving the multi-objective FJSP are verified through the classical example and a mechanical mould job-shop scheduling.