Genetic Algorithm for Mulicriteria Optimization of a Multi-Pickup and Delivery Problem with Time Windows

TL;DR

This paper introduces a genetic algorithm approach combined with Pareto dominance to optimize vehicle routing in a multi-pickup and delivery problem with time windows, considering multiple conflicting objectives.

Contribution

It presents a novel genetic algorithm method for multi-criteria optimization of m-PDPTW, incorporating Pareto dominance to generate diverse optimal solutions.

Findings

Effective in minimizing total travel cost

Reduces total tardiness time

Optimizes number of vehicles used

Abstract

In This paper we present a genetic algorithm for mulicriteria optimization of a multipickup and delivery problem with time windows (m-PDPTW). The m-PDPTW is an optimization vehicles routing problem which must meet requests for transport between suppliers and customers satisfying precedence, capacity and time constraints. This paper purposes a brief literature review of the PDPTW, present an approach based on genetic algorithms and Pareto dominance method to give a set of satisfying solutions to the m-PDPTW minimizing total travel cost, total tardiness time and the vehicles number.