【摘要】 奶制品加工厂主要从总部采购鲜奶(生产),也会从当地奶农采购部分鲜奶(外包)。出于能力和策略的考虑,两种来源的鲜奶采购量均有限;考虑到客户允许奶制品延期交货,相应的鲜奶也可延期交货,生产、外包和库存/延期交货成本均为一般凹函数,问题是以最小的总成本来满足规划期的鲜奶需求。为求解该问题,设计了一种新的基于群体可行状态和个体约束违背程度的自适应惩罚方案,据此设计了求解该问题的遗传算法。为测试算法的性能,先进行了算子组合和遗传算子概率的选择实验,选出最适合的算子和算子概率;在此基础上,针对4个问题实例,通过50次运行,测试了所提自适应罚函数相对4种常见罚函数的优势。更多还原

【Abstract】 The dairy processing plant purchases raw milk mainly from its headquarters,sometimes from local market,where the former can be viewed as production and the latter as outsourcing.Owing to the production capacity and management policy,both production and outsourcing levels are bounded.Raw milk supply can be backlogged because of dairy postponement allowed by customers.All of production,outsourcing and inventory/backlogging costs were as general concave functions. The problem was to satisfy all demands in the planning horizon by minimum total costs. To solve the problem,a novel adaptive penalty scheme was devised based on the feasible status of population and the degree of constraint violation for individuals.Furthermore, a new adaptive genetic algorithm was developed to solve the constrained optimization problem by using the penalty scheme.In order to test the performance of the proposed algorithm,we first made a selection examination to obtain the fittest operator combination and genetic operators’ probabilities.Then,for four planning problems,by 50 runs of the algorithm,the advantages of the penalty scheme were verified by comparing with other common four penalty methods.更多还原