解决具有混合约束柔性流水车间调度问题的粒子群优化算法

针对既存在阻塞限制工件又存在无等待约束工件的柔性流水车间调度问题, 提出了一种离散粒子群优化的求解方法。该方法采用基于排列的编码形式, 设计了推进—迭代算法进行解码并计算问题目标值, 利用离散粒子群优化算法进行全局优化, 利用迭代贪婪(iterated greedy, IG)算法提高种群个体的局部搜索能力。此外, 根据问题特点, 提出最早释放优先(first release first, FRF)和最早完工优先(first complete first, FCF)两种机器分配策略。仿真结果表明, 所提出的方法求解混合约束下柔性流水车间调度问题是可行的、有效的。

Particle swarm optimization algorithm for flexible flow shop scheduling problem with mixed constraints

According to the flexible flow shop scheduling problem with blocking and no-wait constraints, this paper proposed a discrete particle swarm optimization (DPSO) algorithm. Based on the permutation based encoding scheme, it designed a forward-iterative algorithm for decoding and obtaining the objective, used DPSO for global optimization, introduced iterated greedy(IG) algorithm to improve the particles'local searching ability. Besides, it put forward the first release first (FRF) and first complete first (FCF) policies for selecting the processing machines. Experiment results show that the proposed method to solve the flexible flow shop scheduling problem with mixed constraints is feasible and effective.