Application of Hippopotamus Optimization Algorithm for the Routing Problem in Drinking Water Factory

This study addresses the increasing demand for drinking water in Thailand and the logistical challenges it presents, such as high transportation costs and routing inefficiencies. It introduces the novel Hippopotamus Optimization Algorithm (HOA), inspired by the behaviors of hippopotamuses, to optimize the routing of delivery trucks in a drinking water factory, aiming to minimize transportation costs while adhering to tight time constraints. The method involves a two-phase approach: exploration and exploitation, which simulates the land and water activities of hippopotamuses, implemented in a water factory in Southern Thailand. The results show that the HOA-DW significantly improves route optimization, outperforming traditional methods like the Differential Evolution (DE) and Discrete Firefly Algorithm (DFA) by reducing delivery distances and operational costs. The key findings indicate that the HOA-DW not only reduces operational expenses and improves routing efficiency but also adapts well to complex logistical challenges, surpassing existing algorithms in both cost-efficiency and computational speed. This study demonstrates the potential of biologically inspired algorithms in revolutionizing logistics management in the drinking water sector and possibly other industries with similar distribution challenges. The success of the HOA-DW underscores its applicability in logistical operations where efficiency and cost reduction are crucial, encouraging further research into innovative solutions for managing complex logistical demands efficiently.