Thesis Title: Hyperconnected Fresh Supply Chains: Logistics & Market Expansion Frameworks
Dr. Benoit Montreuil, School of Industrial and Systems Engineering, Georgia Tech
Dr. Alan Erera, School of Industrial and Systems Engineering, Georgia Tech
Dr. Chelsea (Chip) White, School of Industrial and Systems Engineering, Georgia Tech
Dr. Pascal Van Hentenryck, School of Industrial and Systems Engineering, Georgia Tech
Dr. Walid Klibi, Kedge Business School, Bordeaux, France
Date and Time: April 22nd, 2021 11:00 AM
Meeting URL: https://bluejeans.com/702725249
Meeting ID: 702725249
This thesis contributes novel frameworks that utilize transdisciplinary approaches to Fresh Supply Chain and Logistics Problems via Operations Research, GIS and Strategic Management. These fresh supply chain frameworks help build market deployment roadmaps, hub location in local supply chains and sustainable logistics strategies. Our study helps to provide solution approaches that are directly implementable in Industry.
In Chapter 1, we address the increasing corporate pressure to be environmentally sustainable. Fresh supply chains face special considerations with decay and loss of quality in perishable products that can occur in transit. We provide a logistics framework that both suppliers and purchasers can utilize to improve the sustainability of their supply chain. We employ customer segmentation, decay & quality modeling, and life cycle analysis (LCA) to help companies rethink their logistics strategies to better align with environmentally sustainable practice. In this chapter, we apply our framework to case studies concerning fresh cut flowers and quick service restaurants.
In Chapter 2, we propose a market deployment framework which outlines a company’s dynamic expansion plan. We build a complementary solution approach that is made up of Executive Factors, Market Ranking, Optimization and Heuristic Models with Dynamic Capabilities. This framework results in a series of alternative solution roadmaps that identify which markets should be deployed in each time phase over a given time horizon. We apply our framework to a case study of a platform which enables local food supply chains by connecting farmers directly to restaurants.
In Chapter 3, we provide a Hybrid OR & GIS methodological framework to the Dynamic (Mobile) Hub Location Problem in the context of a small-scale local food supply chain network. In our hybrid approach, we formulate our network as a p-hub median problem alongside the use of Kernel Density Analysis for hub placement in the network in the case of p = 1. We evaluate our hub effectiveness through a comparison between historical distribution flows (without a mobile hub), expected stagnant hub routes and expected mobile hub routes (both via TSP Heuristics utilizing real road distance).
Ph.D. Candidate Industrial Engineering - Supply Chain Engineering Track