Maritime Dynamic Resource Allocation and Risk Minimization Using Visual Analytics and Elitist Multi-Objective Optimization

Mayamin Raha, Md. Sayed, Monica Nicolescu, Mircea Nicolescu, Sushil Louis

2023

Abstract

Enhancing the safety of protected regions around Navy vessels is one of the most challenging research topics in maritime domains. Robust tactical resource allocation depends on understanding of how the placement, configurations, orientations of multiple assets affect both the area and intensity of coverage around the ships. Towards this end, we built a unique resource allocation problem where we apply a randomized genetic algorithm for searching through a space of 2144 possible parameters representing area coverage, orientation of 6 tactical assets. Our elitist genetic algorithm yielded a maximum fitness value of 90%, 98%, 100% within 50, 150 and 300 generations respectively. Moreover, we put forward a distinctive constrained dynamic resource allocation problem specific to USS Arleigh Burke Destroyer model (DDG-51), where the assets are defenses and coastal guards having binoculars. To solve this, we have used a cross-generational elitist selection based evolutionary algorithm (EA) where our objective is to maximize area of coverage and minimize risk simultaneously. It is a non-deterministic polynomial-time hard (NP-Hard) problem which required searching through a space of 2 48 parameters and resulted in a fitness value of 98% within 35 generations. Furthermore, we present two novel visualization techniques addressing both types of resource allocations.

Paper Citation

in Harvard Style

Raha M., Sayed M., Nicolescu M., Nicolescu M. and Louis S. (2023). Maritime Dynamic Resource Allocation and Risk Minimization Using Visual Analytics and Elitist Multi-Objective Optimization. In Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-670-5, SciTePress, pages 54-63. DOI: 10.5220/0012190100003543

in Bibtex Style

@conference{icinco23,
author={Mayamin Raha and Md. Sayed and Monica Nicolescu and Mircea Nicolescu and Sushil Louis},
title={Maritime Dynamic Resource Allocation and Risk Minimization Using Visual Analytics and Elitist Multi-Objective Optimization},
booktitle={Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2023},
pages={54-63},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012190100003543},
isbn={978-989-758-670-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - Maritime Dynamic Resource Allocation and Risk Minimization Using Visual Analytics and Elitist Multi-Objective Optimization
SN - 978-989-758-670-5
AU - Raha M.
AU - Sayed M.
AU - Nicolescu M.
AU - Nicolescu M.
AU - Louis S.
PY - 2023
SP - 54
EP - 63
DO - 10.5220/0012190100003543
PB - SciTePress