Multi-trip algorithm for multi-depot rural postman problem with rechargeable vehicles

Fuente: arXiv
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Auteurs principaux: Sathyamurthy, Eashwar, Herrmann, Jeffrey W., Azarm, Shapour
Format: Preprint
Publié: 2023
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author Sathyamurthy, Eashwar
Herrmann, Jeffrey W.
Azarm, Shapour
author_facet Sathyamurthy, Eashwar
Herrmann, Jeffrey W.
Azarm, Shapour
contents This paper studies an extension of the rural postman problem with multiple depots and rechargeable and reusable vehicles capable of multiple trips with capacity constraints. This paper presents a new Mixed Integer Linear Programming (MILP) formulation to find optimal solutions to the problem. The paper also proposes a new heuristic called the multi-trip algorithm for the problem whose solutions are compared against solutions of heuristics from literature and the optimal solutions obtained from the MILP formulation by testing them on both benchmark instances and real-world instances generated from road maps. Results show that the proposed heuristic was able to solve all the instances and produce better solutions than heuristics from the literature on 37 of 39 total instances. Due to the high requirement of memory and compute power, the Gurobi optimizer used for solving the MILP formulation, although it produced optimal solutions, was only able to solve benchmark instances but not real-world instances.
format Preprint
id arxiv_https___arxiv_org_abs_2303_03481
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Multi-trip algorithm for multi-depot rural postman problem with rechargeable vehicles
Sathyamurthy, Eashwar
Herrmann, Jeffrey W.
Azarm, Shapour
Multiagent Systems
This paper studies an extension of the rural postman problem with multiple depots and rechargeable and reusable vehicles capable of multiple trips with capacity constraints. This paper presents a new Mixed Integer Linear Programming (MILP) formulation to find optimal solutions to the problem. The paper also proposes a new heuristic called the multi-trip algorithm for the problem whose solutions are compared against solutions of heuristics from literature and the optimal solutions obtained from the MILP formulation by testing them on both benchmark instances and real-world instances generated from road maps. Results show that the proposed heuristic was able to solve all the instances and produce better solutions than heuristics from the literature on 37 of 39 total instances. Due to the high requirement of memory and compute power, the Gurobi optimizer used for solving the MILP formulation, although it produced optimal solutions, was only able to solve benchmark instances but not real-world instances.
title Multi-trip algorithm for multi-depot rural postman problem with rechargeable vehicles
topic Multiagent Systems
url https://arxiv.org/abs/2303.03481