Optimal Resource Allocation within Peri-Urban Consumers with the help of Mine Burst and Glow Worm Optimization Technique

Authors : Amarjit Sau*,Dr.Tilottama Chakrabarty** and Dr.Mrinmoy Majumder***

*Phd Scholar, Hydroinformatics engineering, Civil Engineering Department, NIT Agartala,India

** Assistant Professor,School of Hydroinformatics Engineering(under Civil Dept),NIT Agartala,India

** Associate Professor,School of Hydroinformatics Engineering(under Civil Dept),NIT Agartala,India

Abstract

This study presents a framework for efficient resource distribution among key consumer groups: residents, tourists, aquaculture, livestock, wildlife, and invertebrates. The Analytic Hierarchy Process (AHP) is employed to prioritize these consumers based on their economic and environmental significance. The optimization process compares the performance of the Glowworm Optimization (GWO) and Mine Blast Algorithm (MBA) in determining the most effective resource allocation. Results show that GWO achieves a more balanced allocation compared to MBA. However, MBA excels in specific scenarios with fewer resource constraints. The project demonstrates the utility of GWO for resource management, though challenges such as limited data accuracy and real-world validation persist. Future work will involve refining the model with empirical data and addressing dynamic influences like climate change and seasonal impacts to enhance the robustness of the resource allocation strategy.

53 Ideas of Research Project in Artificial Intelligence and Water Resources(Adv.)