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Design of reverse logistics networks under uncertainty: Multi-objective approach

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posted on 11.05.2022, 14:50 authored by Babak Mohamadpour Tosarkani

A reverse logistics network (RLN) is defined as the backward flow of products, specifically the products that are returned for recycling. Several entities are involved in a recycling process such as regional collection depots, recovery centers, remanufacturing plants, and disposal centers. The main objective of RLN design is to facilitate the reclamation of used products for the purpose of saving cost, energy, resources, and diverting waste from landfills and waterways. On this matter, decision-makers should consider different types of parameters (i.e., fixed and variable costs, the quantity of demand and return, and the quality of returned products) affecting the configuration of facility location models.

In real life, there are a variety of ambiguities associated with mentioned parameters that stem from either internal or external factors (e.g., volatility in market demand, rate of the returned products, unit transportation cost). The main objective of this dissertation is to develop multi- objective optimization models under uncertainty. In this regard, some integrated solution methodologies are introduced to address different types of uncertainty in five stewardship programs (i.e., electronic recycling association (ERA), Canadian battery association (CBA), beverage container stewardship program regulation (BCSPR), Ontario electronic stewardship (OES), wastewater management in hydraulic fracturing) in Canada. 

To consider the environmental impact of such stewardship programs, the proposed mathematical models are extended to the multi-objective optimization models. In this regard, the proposed solution methodologies make decision-makers capable of optimizing the environmental aspects (e.g., green practices of third parties, carbon emissions) associated with RLNs.

History

Language

English

Degree

Doctor of Philosophy

Program

Mechanical and Industrial Engineering

Granting Institution

Toronto Metropolitan University

LAC Thesis Type

Dissertation

Thesis Advisor

Saman Hassanzadeh Amin