Multi-Objective Mixed-Integer Linear Programming for Dynamic Fleet Scheduling, Multi-Modal Transport Optimization, and Risk-Aware Logistics

Nawaf Mohamed Alshabibi, Al-Hussein Matar and Mohamed H. Abdelati ()
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Nawaf Mohamed Alshabibi: Urban and Regional Planning Department, College of Architecture and Planning, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia
Al-Hussein Matar: Automotive and Tractors Engineering Department, Faculty of Engineering, Minia University, Minya 61519, Egypt
Mohamed H. Abdelati: Automotive and Tractors Engineering Department, Faculty of Engineering, Minia University, Minya 61519, Egypt

Sustainability, 2025, vol. 17, issue 10, 1-16

Abstract: Transportation planning is a complex process that aims to achieve the maximum level of effectiveness in terms of costs, usage of transport resources, reliability of deliveries, and minimizing the negative impact on the environment. Most traditional models focus on cost minimization at the expense of risk, road dynamics, and emissions constraints. In contrast, the current paper presents a mixed-integer linear programming (MILP) model for scheduling fleets, selecting transportation modes in multiple modes of transportation, and meeting emissions regulation requirements according to dynamic transportation requirements. Risk-aware routing and taking the factor of congestion and CO 2 emission limits proposed by the government into consideration, this model can offer a more efficient and flexible optimization strategy. From the case study, we observe the significant result that the proposed model achieves, a 23% reduction in transport costs, a 25% improvement in fleet use, a 33.3% decrease in the delivery delay, and a 24.6% decrease in CO 2 emissions. The model dynamically delivers shipments utilizing both road and rail transportation and improves mode choice by minimizing idle vehicle time. This is confirmed through sensitivity analysis which addresses factors such as traffic congestion, changing fuel prices, and changing environmental standards.

Keywords: mixed-integer linear programming; fleet scheduling; multi-modal transport optimization; risk-aware logistics; CO 2 emissions reduction (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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