关键词: 生产批量计划, 量子进化算法, 旋转角, 约束违反度

Abstract: An improved quantum-inspired evolutionary algorithm was proposed to solve lot size scheduling problem, against Genetic Algorithm(GA)and Particle Swarm Optimization(PSO)algorithm falling in the convergence to the local optimal solution. Decision variables of the product planning output in each period were encoded with amplitude amplifications. During iterative solution process, dominance relationships of individuals were compared to the constraint violation degree, which guided population convergence to the reasonable solution. Meanwhile the quantum collapse was controlled by the mechanism of dynamically adjusting rotation angle according to current iteration times. In the later phase of evolution, to speed up convergence, genetic information of the optimal individual was saved as much as possible. Experimental results verified the effectiveness of this algorithm.

Key words: lot size scheduling, quantum evolutionary algorithm, rotate angle, violation value of constraint, integer programing