Robust Optimization applied to the Vehicle Allocation Problem

• Grant number: 22/16817-5
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: July 01, 2023
• End date: February 28, 2025
• Field of knowledge: Engineering - Production Engineering - Operational Research
• Principal Investigator: Pedro Augusto Munari Junior
• Grantee: Enzo Canesso Geraldini
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
• Associated research grant: 22/05803-3 - Cutting, packing, lot-sizing, scheduling, routing and location problems and their integration in industrial and logistics settings, AP.TEM

Abstract

The formulation of mathematical models and algorithms to solve the Vehicle Allocation Problem (VAP) has been an important tool in the decision of fleet allocation. Those decisions can act to decrease the number of empty container trips that, in turn, increase the logistical costs for the company, and also promotes the availability of products in the demanding distribution centers. In this type of problem, parameter uncertainties are inherent. For example, the travel time between two centers, even though the same route is always taken, can vary due to road conditions, traffic, climate, etc. Thus, the optimal solutions achieved in deterministic approaches, although feasible regarding the date provided, are often infeasible in real-world scenarios. To overcome this, one can make use of the Robust Optimization (RO) technique, which helps in modeling and solving problems where parameter uncertainties are a concern, increasing the chances of finding a feasible solution in real-world scenarios. Different from other approaches of optimization under uncertainties, RO does not require the use of probability distributions to represent the random parameters. The objective of this project is to propose RO models for the VAP under uncertainties, making it possible to obtain solutions immune to data variability and, thus, supporting the decision-making process. To this moment, we are not aware of any other RO approach to tackle the VAP under uncertainty.