Unbalanced supply chain design using the analytic network process and a hybrid heuristic-based algorithm with balance modulating mechanism
Unbalanced supply chain design using the analytic network process and a hybrid heuristic-based algorithm with balance modulating mechanism
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DOI：
10.1504/ijbic.2011.038703
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发表时间：
2011-01-01
影响因子：
3.5
通讯作者：
Cui, Zhihua
中科院分区：
文献类型：
--
作者：
Che, Z. H.;Cui, Zhihua
在这项研究中，一个优化的数学模型，提出了基于单产品和多级不平衡系统的供应链设计问题，并考虑四个标准，包括成本，质量，交货时间和合作伙伴关系管理（PRM），以及决策因素，如数量折扣和能力限制。为了提取PRM评价的关键因素，并估计标准之间的相对权重，利用网络分析法（ANP）。此外，我们提出了一个基于遗传算法（GA）和粒子群优化（PSO）算法的混合动力的基础上，通过引入平衡调节（BM）机制来解决的数学模型，找到最优的供应链网络模式，称为GP-TBM。在GP-TBM中，参数设计采用田口方法。最后，以{4-3-3-3}供应链网络结构为例，验证了该方法的有效性，并与标准PSO和GA算法进行了比较。实证分析结果表明，GP-TBM是上级优于标准粒子群算法和遗传算法在所提出的供应链规划问题。
In this study, an optimisation mathematical model is developed for presenting the supply chain design problem which is based on a single-product and multi-echelon unbalanced system, and considering four criteria, including cost, quality, delivery time and partner relationship management (PRM), as well as decision factors such as quantity discount and capacity limits. To extract critical factors of PRM evaluation and estimate relative weight among the criteria, the analytic network process (ANP) is utilised. In addition, we propose a heuristic-based approach, called GP-TBM, based on a hybrid of the genetic algorithm (GA) and particle swarm optimisation (PSO) algorithm by introducing the balance modulating (BM) mechanism to solving the mathematical model to find the optimal supply chain network pattern. In the GP-TBM, the parameters are designed by the Taguchi method. Finally, a case of a {4-3-3-3} supply chain network structure is used to demonstrate the effectiveness of the proposed approach, and GP-TBM compared with standard PSO and GA. The empirical analysis results demonstrate GP-TBM is superior to standard PSO and GA in the proposed supply chain planning problems.