计算机科学
网络规划与设计
外包
数学优化
逆向物流
随机模拟
运筹学
随机规划
整数规划
供应链网络
功能(生物学)
供应链
工业工程
供应链管理
工程类
数学
计算机网络
算法
进化生物学
生物
统计
政治学
法学
作者
Ali Çetin Suyabatmaz,F. Tevhide Altekin,Güvenç Şahin
标识
DOI:10.1016/j.cie.2014.01.004
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI