A1 Refereed original research article in a scientific journal
Genetic Algorithm Based Multipath Optimization for Multimobile Robot Navigations
Authors: Somasundaram, K.; Plosila, Juha
Publisher: Wiley
Publication year: 2026
Journal: Engineering Reports
Article number: e70648
Volume: 8
Issue: 2
eISSN: 2577-8196
DOI: https://doi.org/10.1002/eng2.70648
Publication's open availability at the time of reporting: Open Access
Publication channel's open availability : Open Access publication channel
Web address : https://doi.org/10.1002/eng2.70648
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/515669217
Self-archived copy's licence: CC BY
Self-archived copy's version: Publisher`s PDF
Multimobile Robot Flow Network Problem (MM-RNP) is to find optimum navigation paths in a network without robot collisions. Very few works have been done for the multirobots path allocation problem. Most of the work concentrated on the single robot path allocation problem. This MMRNP is one of the hardest combinatorial optimization problems. MMRNP solutions can be derived using exhaustive enumeration and branch-and-bound linear programming methods. However, the computation required by these procedures is enormous even for a small size problem. In this paper, we present a heuristic approach using Genetic Algorithm (GA) to achieve the near-optimal solution. We propose a new population initialization for our GA with different operators. The proposed GA optimizes path allocation for mobile robots navigating in a static network environment. We follow the edge-level perspective to solve the MMRNP. Our experimental results show that the proposed method gives a better navigation strategy than the traditional methods.
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Funding information in the publication:
This work was supported by the University of Turku, Finland.
