MIT-Zaragoza Speaker Series: Tevhide Altekin

Tevhide Altekin
Assistant Professor of Operations Management
Faculty of Management
Sabanci University, Istanbul, Turkey

 

 

Hybrid Simulation/Analytical Models for Reverse Logistics Network Design of a 3PL

The assessment of the impact of recent environmental legislations on the treatment End-of-life Vehicles and Waste of Electrical and Electronic Equipment has demonstrated that companies are currently using recycling-oriented approaches. This recycling-oriented approach requires the design of a Reverse Logistics (RL) system rather than the design of closed loop system that is plausible for a remanufacturing-oriented approach. The reverse logistics activities in these systems involve collecting end-of life products, testing/sorting and redistribution of the sorted products for legitimate recovery options. A major distinction of these systems entails supply uncertainty in timing, quantity and quality of the end-of life products.
In this study, we consider a manufacturer that has strategically decided to outsource the company specific RL activities to a third-party logistics (3PL) service provider. Given the locations of the collection centers and reprocessing plants, 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. 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. (Joint work Ali Cetin Suyabatmaz and Guvenc Sahin, Faculty of Engineering and Natural Sciences, Sabanci University)

Bio

F. Tevhide Altekin is an Assistant Professor of Operations Management at School of Management, Sabanci University. She received her B.S., M.S. and Ph.D. degrees in industrial engineering from Middle East Technical University. Her research focuses on assembly and disassembly line design, production planning and design of reverse logistics networks. Her work on disassembly line balancing and capacitated lot sizing problem with setups has been published in International Journal of Production Research and OR Spectrum. Currently, she is interested in solving stochastic assembly/disassembly line balancing problems using stochastic programming and hybrid simulation/optimization approaches. She teaches MBA and undergraduate level courses in operations management, business process analysis and design, introduction to management, and business simulation and data analysis. She attends the yacht sailing races organized by the Turkish Offshore Racing Club since 2006 and has ran her first half-marathon in 2011.