A MODIFIED INTELLIGENT WATER DROPS ALGORITHM FOR MULTIPLE OBJECTIVES MULTIPLE DEPOT OPEN VEHICLE ROUTING PROBLEM - Santiyuda, Kadek Gemilang; Chou, Yu-en; Anggara Putra, I Wayan Kintara (Proceeding International Conference on Information Technology, Multimedia, Architecture, Design, and E-Business, 2024)
The delivery cost was once the only concern in transportation, but as society needs to grow, multiple objectives are to be considered in route planning. The efforts of companies to optimize their transportation issues also grow. One of the efforts is to utilize transportation services without directly owning any vehicle and courier to cut management and maintenance costs. The outsourcing of vehicles and couriers to solve multiple objectives of route planning can be formulated into multiple objectives of multiple depot vehicle routing problems (MDOVRP). In this research, a modification of intelligent water drops (IWD) is proposed to find a set of reasonable solutions in the sense of Pareto optimality (Pareto front, PF) for the multiple objectives of MDOVRP. The proposed method applies simulated annealing (SA) probability and a PF optimization method called SPEA2 into IWD (MO-IWDSA). The proposed method is then tested by modifying the hybrid multiple objective evolutionary algorithm (HMOEA) (Bi, Han dan Tang, 2017). The two methods are tested to solve multiple objectives of MDOVRP, an online catering company in Jakarta. The proposed method proved to show improvement in the quality of PF up to 6.4%. The researchers tested their new method with a real-world example: an online catering service in Jakarta. The method uses advanced algorithms inspired by natural processes, like how rivers find the easiest path to flow, combined with other mathematical tools. The result? A better delivery system that improved efficiency by 6.4%, helping the company save money and serve customers faster.