CAJ | 학술논문

作业车间调度问题是一类典型的组合优化问题，要求多个作业在不同的机器上进行加工，目的是获得最好的作业加工序列，以满足特定的性能指标。柔性作业车间调度问题是对传统的作业车间调度问题的进一步扩展，由于求解的复杂性，使得传统方法很难在有效的时间内获得问题的最优解。人工蜂群算法是近年来提出的一种受生物行为启发的优化算法，该算法主要通过模拟蜜蜂的觅食来实现问题的求解。提出了一种离散的人工蜂群算法于求解柔性作业车间调度问题，算法通过交叉方式来搜索潜在的更好的蜜源，并采用自适应的变异策略来降低早熟收敛的可能性。最后通过对比实验证明算法对于求解多目标柔性作业车间调度问题是有效的。
작업차간조도문제시일류전형적조합우화문제，요구다개작업재불동적궤기상진행가공，목적시획득최호적작업가공서렬，이만족특정적성능지표。유성작업차간조도문제시대전통적작업차간조도문제적진일보확전，유우구해적복잡성，사득전통방법흔난재유효적시간내획득문제적최우해。인공봉군산법시근년래제출적일충수생물행위계발적우화산법，해산법주요통과모의밀봉적멱식래실현문제적구해。제출료일충리산적인공봉군산법우구해유성작업차간조도문제，산법통과교차방식래수색잠재적경호적밀원，병채용자괄응적변이책략래강저조숙수렴적가능성。최후통과대비실험증명산법대우구해다목표유성작업차간조도문제시유효적。
The job shop scheduling problem is one of the most classical combinatorial optimization problems,which con-cerns allocation of a set of jobs on a set of machines to meet certain criteria. Flexible job shop scheduling problem (FJSSP) is an extension of JSSP and very difficult to achieve an optimal solution with traditional optimization approach-es owing to the high computational complexity. Artificial bee colony (ABC) algorithm invented recently is a biologi-cal-inspired optimization algorithm,which simulates the foraging behaviors of honey bee swarm. A discrete artificial bee colony algorithm (DABC) is proposed to solve multi-objective flexible job shop scheduling problem. In DABC, the crossover strategy is introduced to search for the better solution (food source). Besides,an adaptive mutation strategy is adopted to overcome the shortcoming of premature convergence. Finally, the proposed algorithm is tested on different scale problems and compared with the proposed efficient algorithms in the literature recently. The results show that DP-SO is an effective and efficient.