Solving a Two-stage Supply Chain Network Design Problem with Fixed Costs by a Hybrid Genetic Algorithm

Ovidiu Cosma, P. Pop, C. Sabo
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Abstract

In this paper we investigate a particular two-stage supply chain network design problem with fixed costs. In order to solve this complex optimization problem, we propose an efficient hybrid algorithm, which was obtained by incorporating a linear programming optimization problem within the framework of a genetic algorithm. In addition, we integrated within our proposed algorithm a powerful local search procedure able to perform a fine tuning of the global search. We evaluate our proposed solution approach on a set of large size instances. The achieved computational results prove the efficiency of our hybrid genetic algorithm in providing high-quality solutions within reasonable running-times and its superiority against other existing methods from the literature.
用混合遗传算法求解具有固定成本的两阶段供应链网络设计问题
本文研究了一类具有固定成本的两阶段供应链网络设计问题。为了解决这一复杂的优化问题,我们提出了一种高效的混合算法,该算法将线性规划优化问题纳入遗传算法的框架中。此外,我们在我们提出的算法中集成了一个强大的局部搜索过程,能够对全局搜索进行微调。我们在一组大型实例上评估我们提出的解决方案方法。所取得的计算结果证明了混合遗传算法在合理的运行时间内提供高质量解的效率,以及与文献中其他现有方法相比的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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