Huang Song, Tian Na, Wang Yan, Ji Zhicheng
School of Internet of Things Engineering, Jiangnan University, 1800 Lihu Avenue, Wuxi, Jiangsu Province 214122 China.
School of Internet of Things Engineering, Jiangnan University, 1800 Lihu Avenue, Wuxi, Jiangsu Province 214122 China ; Engineering Research Center of Internet of Things Technology Applications, Ministry of Education, Jiangnan University, Wuxi, 214122 China.
Springerplus. 2016 Aug 30;5(1):1432. doi: 10.1186/s40064-016-3054-z. eCollection 2016.
Taking resource allocation into account, flexible job shop problem (FJSP) is a class of complex scheduling problem in manufacturing system. In order to utilize the machine resources rationally, multi-objective particle swarm optimization (MOPSO) integrating with variable neighborhood search is introduced to address FJSP efficiently. Firstly, the assignment rules (AL) and dispatching rules (DR) are provided to initialize the population. And then special discrete operators are designed to produce new individuals and earliest completion machine (ECM) is adopted in the disturbance operator to escape the optima. Secondly, personal-best archives (cognitive memories) and global-best archive (social memory), which are updated by the predefined non-dominated archive update strategy, are simultaneously designed to preserve non-dominated individuals and select personal-best positions and the global-best position. Finally, three neighborhoods are provided to search the neighborhoods of global-best archive for enhancing local search ability. The proposed algorithm is evaluated by using Kacem instances and Brdata instances, and a comparison with other approaches shows the effectiveness of the proposed algorithm for FJSP.
考虑到资源分配，柔性作业车间问题（FJSP）是制造系统中的一类复杂调度问题。为了合理利用机器资源，引入了结合可变邻域搜索的多目标粒子群优化算法（MOPSO）来有效解决FJSP。首先，提供分配规则（AL）和调度规则（DR）来初始化种群。然后设计特殊的离散算子来产生新个体，并在扰动算子中采用最早完工机器（ECM）以跳出局部最优。其次，通过预定义的非支配存档更新策略更新的个人最佳存档（认知记忆）和全局最佳存档（社会记忆），同时被设计用于保存非支配个体并选择个人最佳位置和全局最佳位置。最后，提供三个邻域来搜索全局最佳存档的邻域以增强局部搜索能力。通过使用Kacem实例和Brdata实例对所提出的算法进行评估，与其他方法的比较表明了所提出算法对FJSP的有效性。
