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Modeling a Cooperative Location-routing Problem under Multi-echelon Supply Chain Disruption Risk

Modeling a Cooperative Location-routing Problem under Multi-echelon Supply Chain Disruption Risk
Evangelos I. Kaisar, Ph.D. (PI)
Professor, Department of Civil, Environmental and Geomatics Engineering
Florida Atlantic University
ekaisar@fau.edu
Dan Liu, Ph.D.
Postdoctoral Researcher, Department of Civil and Environmental Engineering
Florida Atlantic University
liud@fau.edu

 

Proposal Summary and Objectives

Increasing concerns about supply chain disruptions caused by unplanned events, such as pandemics, requires advanced models for improving the supply chain resilience. A challenging task is to make plans for the unplanned events in advance because the service capacity of each supplier–distributor varies randomly due to a variety of possible disruptions. Horizontal collaboration can take advantage of the multi-echelon supply chain network itself and include satisfying demand from an alternate location in the network, or transportation from an alternate source or route. Our interest in this study is to analyze the benefits of horizontal collaboration with multiple suppliers and distributors by developing a decision support model that can address these concerns. The problem is formulated as mixed-integer linear programs (MILPs) related to the Capacity Location Routing Problem (CLRP) and a new hybrid heuristic is designed to find near-optimal solutions for large-sized instances. The goal is to determine the location, allocation, and routing decisions that minimize the cost of location, routing, and the disruption penalty. Furthermore, the proposed approach is applied to scenarios analysis. Numerical experiments will test the aggregated total cost and disruption penalty from cooperation, which is compared to the case where horizontal collaboration does not exist.

Funding Amount: $42,000
Status: Active
Duration: Sep 1, 2020 - Aug 31, 2021