求解批量流水线调度问题的蜂群算法

针对批量流水线调度问题,提出了一种改进的人工蜂群算法来优化最大完成时间。该算法运用NEH方法产生初始解,采用混沌遍历的方法生成新的邻域解。为了跳出局部最优,使用最优解的插入扰动来替换一些连续若干步不能改进的解来提高算法的全局搜索能力。采用自适应的局部搜索加强算法的局部搜索能力。仿真试验表明了所得算法的可行性和高效性。

Artificial bee colony algorithm for lot-streaming flow shop scheduling problem

An Improved Artificial Bee Colony（IABC） algorithm is presented for solving the Lot-streaming Flow Shop Scheduling Problem（LFSP） with the objective of minimizing the maximum completion time,i.e.,makespan.In the proposed IABC algorithm,the famous NEH heuristic is used to produce an initial solution,and the chaos is employed to generate a new candidate.In order to avoid trapping into local optima,the solution not improved in a number of generations in the population is replaced by the perturbation of the best solution found so far.In addition,a self-adaptive local search is presented and imbedded in the IABC algorithm to balance the exploitation and exploration.The computational results show that the IABC algorithm is effective and efficient for the LFSP.