Mutation Management for Evolutionary Small-Moves Approach in Pickup and Delivery Problem
Year: 2023
Type: conference-paper
Abstract: This paper focuses on the Pickup and Delivery Problem in the transportation and logistics industry. The study utilizes evolutionary programming methods and small-moves mutation management to develop algorithms for optimizing vehicle routes. The research investigates the effectiveness of various mutations and strategies by comparing them to existing solutions. During the study, existing mutations and strategies were analyzed and new strategies and mutations were developed. A comprehensive comparison of these strategies and mutations was conducted. By incorporating various reinforcement learning algorithms as strategies, an average reduction in route length by 81% was achieved, surpassing the results of previous studies, which exceeded the results of previous studies by more than 7%. Code is available at https://github.com/xeniabaturina/pdp_python.
Source: Procedia Computer Science
Institution: ITMO University
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4390282970