摘要
讨论一类Job-shop车间的生产计划和调度的集成优化问题,给出了该问题的非线性混合整数规划模型,并采用混合遗传算法进行求解。该模型利用调度约束来细化生产计划,以保证得到可行的调度解。在混合算法中,利用启发式规则来改善初始解集,并采用分段编码策略将计划和调度解映射为染色体。算例研究表明,该算法对求解该类问题具有很好的效果。
An integrated job-shop production planning and scheduling problem with setup time and batches is addressed. A nonlinear mix integer programming model is presented and solved by a hybrid genetic algorithm. In the model, the scheduling constraints are used to make the production planning more accurate, which provides a feasible scheduling. In the hybrid algorithm, the heuristic rules are used to improve the initial solutions, and a subsection coding strategy is offered to convert the planning and scheduling solution into a chromosome. An example shows the effectiveness of the hybrid algorithm.
出处
《控制与决策》
EI
CSCD
北大核心
2003年第5期581-584,共4页
Control and Decision
关键词
成批生产
Job—shop
生产计划和调度
混合遗传算法
Automobile manufacture
Constraint theory
Flexible manufacturing systems
Genetic algorithms
Optimization
Scheduling
