Logistics optimization is essential for improving operational efficiency in industries reliant on transportation. This study focuses on the Pickup and Delivery Problem (PDP), an extension of the Vehicle Routing Problem (VRP), which involves both pickup and delivery tasks. Our research presents a multi-objective optimization approach to address PDPs, incorporating complexities such as alternative pick-up locations and time window constraints. We aim to minimize both delivery lateness and transportation costs using a Mixed-Integer Programming (MIP) model. Our methodology optimizes multiple objectives simultaneously by minimizing both delivery lateness and overall transportation costs. By developing novel approaches to improve logistics operations, this research contributes to advancing transportation optimization and supply chain management, ultimately leading to a more efficient and cost-effective logistics environment.
A Multi-objective Optimization for Efficient Pickup and Delivery Problems: Addressing Alternative Locations and Time Windows
Lecture Notes in Operations res.
International Conference on Operations Research ; 2024 ; Munich, Germany September 02, 2024 - September 05, 2024
12.08.2025
7 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Time Window Constraints , Pickup and Delivery Problem , Logistics Optimization , Multi-Objective Optimization , Alternative Pickup Locations Operations Management , Optimization , Artificial Intelligence , Business and Management , Operations Research, Management Science , Operations Research/Decision Theory , Data Structures and Information Theory
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