关键词: 订单组批, 装箱问题, 遗传算法, 基因段, 铜板带

Abstract: How to tackle the planning order grouping problem effectively became the high priority in copper strip process. Based on the studies of order grouping law in copper strip production, a multi-objective order grouping optimization model was established, which considered ingots'chemical constitution, process routing and economic benefits comprehensively. A modified Genetic Algorithm (GA) based on gene segment was proposed, and the rules of coding, decoding, crossover and mutation based on gene segment were designed. The multi-objective problem was converted to single-objective problem to find the solution by integrating the coincidence degree of ingot's number and process routing. Production data revealed that the number of copper ingots needed and the times of coil stock dividing in middle process were greatly reduced by using the proposed method, and it could solve the order grouping optimization effectively.

Key words: order grouping, bin packing problem, genetic algorithms, gene segment, copper strip