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New and efficient algorithms for transfer prices and inventory holding policies in two-enterprise supply chains

机译:两企业供应链中转移价格和库存持有策略的新型高效算法

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We consider a multi-period problem of fair transfer prices and inventory holding policies in two enterprise supply chains. This problem was formulated as a mixed integer non-linear program by Gjerdrum et al. (Eur J Oper Res 143:582-599, 2002). Existing global optimization methods to solve this problem are computationally expensive. We propose a continuous approach based on difference of convex functions (DC) programming and DC Algorithms (DCA) for solving this combinatorial optimization problem. The problem is first reformulated as a DC program via an exact penalty technique. Afterward, DCA, an efficient local approach in non-convex programming framework, is investigated to solve the resulting problem. For globally solving this problem, we investigate a combined DCA-Branch and Bound algorithm. DCA is applied to get lower bounds while upper bounds are computed from a relaxation problem. The numerical results on several test problems show that the proposed algorithms are efficient: DCA provides a good integer solution in a short CPU time although it works on a continuous domain, and the combined DCA-Branch and Bound finds an ∈-optimal solution for large-scale problems in a reasonable time.
机译:我们考虑两个企业供应链中的公平定价和库存持有政策的多个时期问题。这个问题由Gjerdrum等人制定为混合整数非线性程序。 (Eur J Oper Res 143:582-599,2002)。解决该问题的现有全局优化方法在计算上是昂贵的。我们提出了一种基于凸函数(DC)编程和DC算法(DCA)差异的连续方法来解决此组合优化问题。首先通过精确惩罚技术将问题重新格式化为DC程序。之后,研究了DCA,一种在非凸编程框架中有效的局部方法,以解决由此产生的问题。为了全局解决此问题,我们研究了组合的DCA-分支和边界算法。 DCA用于获得下限,而上限是根据松弛问题计算得出的。若干测试问题的数值结果表明,所提出的算法是有效的:DCA尽管在连续域上运行,但在短CPU时间内提供了一个很好的整数解,而DCA-Branch和Bound的组合则为大型算法提供了ε最优解。在合理时间内解决大规模问题。

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