Time: Dec 25, 2018 (Tuesday) 3 PM
Location：Room 326 in Main Building, SME
Topic: Third-party Reverse Logistics Partner Selection and Order Allocation in the Cellphone Industry
Speaker profile：Dr. Sunil Kumar Jauhar is a Postdoctoral Research Fellow in Operations and Supply Chain Management at Ted Rogers School of Management, Ryerson University, Canada. He received his Undergraduate and Master's Degrees in Industrial Engineering. Following this, he earned his Ph.D. in Operations and Supply Chain Management from the Indian Institutes of Technology Roorkee, India. Dr. Jauhar’s has over three years of academic experience at the national institute of importance NIT Bhopal India, SGSITS Indore India, and CDGI Indore India. His research interests include Third Party Reverse Logistics, Sustainable Supply chain management, Data Envelopment Analysis, Performance Measurement, and Soft computing techniques. He is the author of a book chapter and published 25 plus research papers in various journals and conferences of national and international repute. Dr. Jauhar’s has received several fellowship and scholarships. These include Post-Doc Fellowship of Ted Rogers School of Management Ryerson University Canada, Ph.D. fellowships and Master's scholarships from Ministry of Human Resource and Development Govt. of India and Undergraduate scholarship from Govt. of Madhya Pradesh India. He is an active member of several research societies (e.g., Institute for Operations Research and Management Sciences (INFORMS), Decision Sciences Institute (DSI) and Canadian Operational Research Society (CORS)).
Introduction:
Dr. Jauhar introduces a Non-Parametric method and a Meta-heuristic technique to solve a Third-Party Reverse Logistics Partner (3PRLP) Selection problem. The talk will also draw attention to the process of determining how orders are allocated to each 3PRLP, using a multi-objective mathematical model in the Canadian Cellular Phone industry. The abstract of the lecture is as follows.
End of life (EOL) electronic products companies face growing governing and social pressures to implement reverse logistics (RL) activities in order to develop sustainable supply chains. However, RL activities for EOL electronic products are complicated and require special attention. In recent years, original equipment manufacturers (OEMs) have begun to focus on their RL operations to better meet consumer demand and comply with environmental regulations. Therefore, the role of 3PRLPs has become essential to complex RL operations. Unlike current models in the RL literature, this research simultaneously draws attention to the selection of 3PRLPs and the process of determining how orders are allocated to each 3PRLP, in a comprehensive and novel framework. Our proposed decision-making framework contains two phases. The first phase is a holistic approach that integrates data envelopment analysis (DEA) with a differential evolution (DE) algorithm to increase the discriminatory power and improve the ranking while measuring the efficiencies of 3PRLPs. In the second phase, we utilize the measured efficiencies in the proposed multi-objective mathematical model to allocate orders to 3PRLPs. Two solution approaches are employed to solve the proposed multi-objective model and to find Pareto-optimal solutions. The application of the proposed framework is illustrated in Canada’s cellphone industry.
