Hybrid simulation-analytical modeling approaches for the reverse logistics network design of a third-party logistics provider

被引:56
作者
Suyabatmaz, Ali Cetin [1 ]
Altekin, F. Tevhide [2 ]
Sahin, Guvenc [3 ]
机构
[1] McGill Univ, Desautels Fac Management, Montreal, PQ H3A IG5, Canada
[2] Sabanci Univ, Sch Management, TR-34956 Istanbul, Turkey
[3] Sabanci Univ, Fac Engn & Nat Sci, TR-34956 Istanbul, Turkey
关键词
Reverse logistics; Network design; Supply uncertainty; Hybrid simulation-analytical modeling; PRODUCT RECOVERY; INTEGRATING SIMULATION; PRODUCTION SYSTEM; STOCHASTIC-MODEL; SUPPLY CHAIN; OPTIMIZATION; UNCERTAINTY; OPERATIONS; SCHEDULE; IMPACT;
D O I
10.1016/j.cie.2014.01.004
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this study, we consider a manufacturer that has strategically decided to outsource the company specific reverse logistics (RL) activities to a third-party logistics (3PL) service provider. Given the locations of the collection centers and reprocessing facilities, the RL network design of the 3PL involves finding the number and places of the test centers under supply uncertainty associated with the quantity of the returns. Hybrid simulation-analytical modeling, which iteratively uses mixed integer programming models and simulation, is a suitable framework for handling the uncertainties in the stochastic RL network design problem. We present two hybrid simulation-analytical modeling approaches for the RL network design of the 3PL. The first one is an adaptation of a problem-specific approach proposed in the literature for the design of a distribution network design of a 3PL. The second one involves the development of a generic approach based on a recently proposed novel solution methodology. In the generic approach instead of exchanging problem-specific parameters between the analytical and simulation model, the interaction is governed by reflecting the impact of uncertainty obtained via simulation to the objective function of the analytical model. The results obtained from the two approaches under different scenario and parameter settings are discussed. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:74 / 89
页数:16
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