Abstract: In order to solve the rescheduling problem of flexible job shop inserting orders, a dynamic rescheduling model with the maximum completion time, total energy consumption, total delay time and total equipment changes as objective functions is established, and the weighted sum method is used to normalize the four indicators, an improved imperialist competitive algorithm（I-ICA） is proposed as a global optimization algorithm. On the basis of the traditional imperialist competitive algorithm（ICA）, the empire revolution mechanism is introduced to increase the global search of the algorithm, and the empire elimination mechanism is introduced to accelerate the convergence of the algorithm and the external empire invasion strategy to increase the search breadth of the algorithm, so as to avoid the algorithm falling into “precocious”. For the unprocessed operations after the order insertion point, an event-driven strategy is used to reschedule. Finally, through the verification of production examples, the traditional ICA, genetic algorithm（GA） and particle swarm optimization（PSO） are used as comparison algorithms, the validity and feasibility of I-ICA in solving the flexible job shop insertion order rescheduling problem are verified.

Key words: imperialist competitive algorithm（ICA）, reschedule, intrusion strategy, elimination mechanism

摘要： 为解决柔性作业车间插单重调度问题，建立了以最大完工时间、总能耗、总延迟时间和总设备变更次数为目标函数的动态重调度模型，并对四个目标采用线性加权和法归一化，提出一种改进的帝国竞争算法（improved imperialist competitive algorithm，I-ICA）作为全局优化算法。在传统帝国竞争算法（imperialist competitive algorithm，ICA）的基础上，引入帝国革命机制，来增加算法的全局搜索，同时引入帝国消除机制来加速算法的收敛和外部帝国入侵策略来增加算法的搜索广度，避免算法陷入“早熟”。针对订单插入点后未加工的工序，采用事件驱动策略重新调度。最后通过生产实例验证，将ICA、遗传算法（genetic algorithm，GA）和粒子群算法（particle swarm optimization，PSO）作为对比算法，验证了I-ICA在求解柔性作业车间插单重调度问题上的有效性和可行性。

关键词: 帝国竞争算法, 重调度, 入侵策略, 消除机制