Abstract: For hot rolling batch scheduling of seamless steel tubes,considering the constraints of production process,a multi-objective optimization integer programming model was established to minimize the roller consumption and the tardiness of the rolling units.The influence of batch scheduling sequence of seamless steel tubes on the roller consumption was analyzed.A heuristic algorithm was proposed for solving the given rolling batch problem,and a Learnable Memetic Algorithm (LMA) with multi-population was designed.The different search operators and adaptive selection strategies were designed to guide the population evolution for the objective.Simulative experiments and the comparison with Non-Dominated Sorting Genetic Algorithms Ⅱ (NSGA-Ⅱ) and Memetic Algorithm (MA) illustrated the effectiveness of the proposed LMA.

Key words: seamless steel tube, batch scheduling, multi-objective optimization, learnable memetic algorithm

摘要： 针对无缝钢管热轧批量调度问题,考虑生产工艺约束、生产需求优化等因素,以最小化热工具轧辊使用消耗、生产拖期为目标,建立了多目标整数规划模型。分析了无缝钢管批量调度顺序对热工具轧辊消耗的影响,给定了轧制批量顺序下的求解启发式算法,并设计了一种基于多种群进化的学习型文化基因算法。针对目标设计了不同的搜索算子以及算子的自适应学习选择策略来指导种群进化,充分发挥全局搜索和局部搜索能力。仿真实验与常用的带精英策略的快速非支配排序遗传算法和文化基因算法进行了对比,验证了所提模型和算法的有效性。

关键词: 无缝钢管, 批量调度, 多目标优化, 学习型文化基因算法