Decision support for build-to-order supply chain management through multiobjective optimization

被引:51
|
作者
Mansouri, S. Afshin [1 ]
Gallear, David [1 ]
Askariazad, Mohammad H. [2 ]
机构
[1] Brunel Univ, Brunel Business Sch, Uxbridge UB8 3PH, Middx, England
[2] Sharif Univ Technol, Sch Management, Kish Isl, Iran
关键词
Supply chain management; Build-to-order; Decision support; Multiobjective optimization; Pareto-optimal front; GENETIC ALGORITHM APPROACH; SIMULATION-BASED OPTIMIZATION; INVENTORY MANAGEMENT; MASS CUSTOMIZATION; DESIGN; SYSTEMS; PERFORMANCE; FRAMEWORK; NETWORKS; PRODUCTS;
D O I
10.1016/j.ijpe.2010.11.016
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets. Crown Copyright (C) 2010 Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:24 / 36
页数:13
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