Multi-Objective Meta-Heuristic Approach supported by an Improved Local Search Strategy for the Design and Planning of Supply Chain Networks

被引：0
|
作者：
Chibeles-Martins, Nelson [1 ,3 ]
Pinto-Varela, Tania [1 ,2 ]
Barbosa-Povoa, Ana Paula [2 ]
Novais, A. Q. [1 ,2 ]
机构：
[1] UAER LNEG, Estr Paco Lumiar 22, P-1649038 Lisbon, Portugal
[2] Univ Lisbon, Inst Super Tecn, CEG IST, P-1049001 Lisbon, Portugal
[3] Univ Nova Lisboa, Fac Ciencias & Tecnol, Ctr Math & Applicac, P-2829516 Caparica, Portugal
来源：
24TH EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING, PTS A AND B | 2014年 / 33卷
基金：
美国国家科学基金会;
关键词：
Multi-Objective; Meta-Heuristic; Simulated Annealing; Supply Chain Network; OPTIMIZATION;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
This paper explores alternative strategies for the Local Search mechanism of a Bi-Objective Simulated Annealing Algorithm. The algorithm is adapted to the planning and design of supply chain networks, where the Pareto Frontier approximations generated are compared with those based on an exact approach. Several strategies are proposed to improve the algorithm performance, which are exemplified through the solution of an example. The robustness and versatility of the proposed method is illustrated where a sensitivity analysis on two parameters of the model is performed: Final Product Demand and Facility Capacity.
引用
收藏
页码：313 / 318
页数：6
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