Applications of A New Genetic Algorithm to Solve The Centralized Carrier Collaboration and Multihub Location Problem Considering Environmental Impacts
Abstract
The Centralized Carrier Collaboration and Multi-hub Location Problem (CCCMLP) represents a strategy that small-to-medium sized less-than-truckload (LTL) carrier companies can use in order to improve their profit margins. It is a strategy that is being explored in order to make these companies more sustainable as they are forced to reinvent their processes and supply chains. In this work, I will present a metaheuristic approach to optimizing their hub establishment and routing policies in order to better their expected profit margins and reduce their environmental impacts. The study considers the costs of transportation, loading and unloading, maintenance, operations, and inventory holding as part of the costs incurred by the carriers. Additionally, there is a cost incurred by the establishment of a hub for shipment consolidation. Similarly, there are environmental impacts to be considered. These are to be represented and accounted for in terms of the Global Warming Potential (GWP) they represent. Optimality in the results will be represented by a Pareto front, which will be compared with some single-objective solutions for reference. The objective of the CCCMLP is to seek a set of hybrid collaborative consolidation transshipment hubs with the purpose of establishing a collaborative hybrid hub-and-spoke network system to minimize the aforementioned parameters. The problem is modeled using Universal Generating Functions (UGFs) for the stochastic variables and solved using a Multi-Objective Evolutionary Algorithm (MOEA).
Subject Area
Industrial engineering|Operations research|Transportation
Recommended Citation
Castillo Fatule, Eduardo Jose, "Applications of A New Genetic Algorithm to Solve The Centralized Carrier Collaboration and Multihub Location Problem Considering Environmental Impacts" (2019). ETD Collection for University of Texas, El Paso. AAI22582813.
https://scholarworks.utep.edu/dissertations/AAI22582813