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Lot sizing with piecewise concave production costs

机译:分批凹进生产成本的批量

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摘要

We study the lot-sizing problem with piecewise concave production costs and concave holding costs. This problem is a generalization of the lot-sizing problem with quantity discounts, minimum order quantities, capacities, overloading, subcontracting or a combination of these. We develop a dynamic programming algorithm to solve this problem and answer an open question in the literature: we show that the problem is polynomially solvable when the breakpoints of the production cost function are time invariant and the number of breakpoints is fixed. For the special cases with capacities and subcontracting, the time complexity of our algorithm is as good as the complexity of algorithms available in the literature. We report the results of a computational experiment where the dynamic programming is able to solve instances that are hard for a mixed-integer programming solver. We enhance the mixed-integer programming formulation with valid inequalities based on mixing sets and use a cut-and-branch algorithm to compute better bounds. We propose a state space reduction-based heuristic algorithm for large instances and show that the solutions are of good quality by comparing them with the bounds obtained from the cut-and-branch. © 2014 INFORMS.
机译:我们研究了具有分段凹面生产成本和凹面持有成本的批量问题。此问题是批量折扣问题的普遍化,包括数量折扣,最小订单数量,容量,超载,分包或这些的组合。我们开发了一种动态规划算法来解决该问题,并回答了文献中的一个悬而未决的问题:我们证明,当生产成本函数的断点为时间不变且断点数固定时,该问题可以多项式求解。对于具有能力和分包的特殊情况,我们算法的时间复杂度与文献中可用算法的复杂度一样好。我们报告了一个计算实验的结果,其中动态编程能够解决混合整数编程求解器难以实现的实例。我们基于混合集使用有效不等式增强了混合整数编程公式,并使用分枝算法来计算更好的界限。我们为大型实例提出了一种基于状态空间约简的启发式算法,并通过将其与从割断分支获得的边界进行比较,表明该解决方案具有良好的质量。 ©2014 INFORMS。

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