A tactical supply chain planning model with multiple flexibility options: an empirical evaluation

被引:0
作者
Masoud Esmaeilikia
Behnam Fahimnia
Joeseph Sarkis
Kannan Govindan
Arun Kumar
John Mo
机构
[1] RMIT University,School of Aerospace, Mechanical and Manufacturing Engineering
[2] University of Technology Sydney,UTS Business School
[3] Worcester Polytechnic Institute,WPI School of Business
[4] University of Southern Denmark,Department of Business and Economics
来源
Annals of Operations Research | 2016年 / 244卷
关键词
Supply chain management; Tactical planning; Flexibility; Mathematical modeling; Empirical study;
D O I
暂无
中图分类号
学科分类号
摘要
Supply chain flexibility is widely recognized as an approach to manage uncertainty. Uncertainty in the supply chain may arise from a number of sources such as demand and supply interruptions and lead time variability. A tactical supply chain planning model with multiple flexibility options incorporated in sourcing, manufacturing and logistics functions can be used for the analysis of flexibility adjustment in an existing supply chain. This paper develops such a tactical supply chain planning model incorporating a realistic range of flexibility options. A novel solution method is designed to solve the developed mixed integer nonlinear programming model. The utility of the proposed model and solution method is evaluated using data from an empirical case study. Analysis of the numerical results in different flexibility adjustment scenarios provides various managerial insights and practical implications.
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页码:429 / 454
页数:25
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  • [1] Alemany M. M. E.(2010)Mathematical programming model for centralised master planning in ceramic tile supply chains International Journal of Production Research 48 5053-5074
  • [2] Boj J. J.(2003)An approach for strategic supply chain planning under uncertainty based on stochastic 0–1 programming Journal of Global Optimization 26 97-124
  • [3] Mula J.(2011)Tabu search with path relinking for an integrated production–distribution problem Computers & Operations Research 38 1199-1209
  • [4] Lario F.-C.(2008)Optimization of production allocation and transportation of customer orders for a leading forest products company Mathematical and Computer Modelling 48 1158-1169
  • [5] Alonso-Ayuso A.(2012)A new approach to tactical and strategic planning in production–distribution networks Applied Mathematical Modelling 36 1703-1717
  • [6] Escudero L. F.(1999)Measuring supply chain performance International Journal of Operations & Production Management 19 275-292
  • [7] Garin A.(2010)Application of fuzzy mathematical programming approach to the production allocation and distribution supply chain network problem Expert Systems with Applications 37 4488-4495
  • [8] Ortuno M. T.(2007)Single versus multiple supplier sourcing strategies European Journal of Operational Research 182 95-112
  • [9] Perez G.(2011)Bilevel model for production–distribution planning solved by using ant colony optimization Computers & Operations Research 38 320-327
  • [10] Armentano V. A.(2012)A particle swarm optimization algorithm for solving unbalanced supply chain planning problems Applied Soft Computing 12 1279-1287