Multi-depot dispatch for Routing heuristics using location alloction instance on formulating flood prone demography in Sarawak

Disaster relief logistics is vital for effective disaster preparedness and response, involving strategic depots and distribution networks. Intelligent decision-making optimizes routing and customer targeting, while heuristics predict expenses for round-trip deployments. Recent efforts aim to develop temporary logistics solutions to meet demand and enhance coverage. Presently, distribution networks designed to address the lack of a strategic autonomous intelligent relief distribution network also prioritizes specific proposals that involve tradeoff in prioritizing demographic priorities while optimizing resource allocation for tasks. This research employs computational intelligence to improve a scheduling model for distributing commodities in flood-prone, low-lying divisions of the Sarawak region. To attain minimal resource use and optimal route coverage, the Multi-Depot Vehicle Routing Problem, tailored for this scenario, integrates advanced routing optimization techniques with demographic clustering. The research framework integrates sophisticated data clustering and computational intelligence methods, featuring a variant of the genetic algorithm with repopulation crossovers, alongside several important iterated local search techniques (Clarke-Wright savings algorithm, route relocation, Greedy, and Tabu search) to enhance flood relief routing schedules. The study shows how to enhance flood relief distribution by improving local search heuristics and shortest path estimations. Furthermore, the study augments coverage areas, reduces costs, and increases operational efficiency. The routing heuristic method, combined with autonomous computational intelligence techniques, had positive results for costs and overall routes. The method identifies customer-depot links intelligently whilst adhering to the conditions of an established set of parameters. Ultimately, the study displayed the viability of developing disaster-tailored solutions for flood mitigation selections to deliver relief supplies during phases of crisis response. The study can be considered a proof-of-concept for establishing efficiently a scheduling system coupled with flood mitigation for the Sarawak region, which depends on the related solution heuristics (MDVRP instance) of preceding research.