列生成与GUB相结合求解钢铁原料采购批量问题(英文)

Combine Column Generation with GUB to Solve the Steel-Iron Raw Materials Purchasing Lot-Sizing Problem

钢铁原料采购批量问题的目标是确定各种原料在一定时期(通常为一年)的各个时段(一个月)内的采购量,在满足生产需求的前提下,使总的采购成本和库存费用之和最小。一般批量问题是NP-hard,目前只存在有限的、启发式的方法求解小规模问题.建立了原料采购批量模型并提出一种新的方法——列生成与GUB(广义上界)相结合方法求解该模型.一组实际问题测试结果证明了该方法的有效性,同时也表明了该方法的潜在应用价值.

The objective of steel-iron raw materials purchasing lot-sizing problem is to identify the purchasing quantity of each item in each period over a given horizon so that the total sum of inventory cost and purchasing cost is minimized under considerations. The lot-sizing problems have been proved to be NP-hard. The existing optimal approaches can only solve small-sized problems. We formulate the steel-iron raw materials purchasing lot-sizing problem and propose a new approach combining column generation with GUB (the generated upper bound) to solve the problem. The computational results of a practical problem show that the approach is effective and has potential application values in making purchasing decisions.