<![CDATA[AbstractThis research addresses the Multi Depot Vehicle Routing Problem with Time Windows (MDVRPTW), the problem of determining vehicle routes from several depots to multiple customers while considering time window constraints for each route. The goal of solving MDVRPTW is to obtain optimal routes with the shortest total travel time without exceeding their respective time windows. The Particle Swarm Optimization (PSO) algorithm is used to solve MDVRPTW, adapted from the social behavior of a flock of birds in search of food. The algorithm operates through initialization, evaluation, route construction, and route updates to achieve optimality. The research was tested on a case study involving raw material pickup for a company with 2 storage depots and 169 agents. The implementation of PSO successfully generated an average travel time of 7.83 hours for each route, indicating adherence to time windows and fulfillment of vehicle capacity.Keywords:Multi Depot Vehicle Routing Problem, Particle Swarm Optimization, Route, Time WindowsAbstrakPenelitian ini membahas Multi Depot Vehicle Routing Problem with Time Windows (MDVRPTW), masalah penentuan rute kendaraan dari sejumlah depot ke beberapa pelanggan dengan mempertimbangkan batasan time windows dalam setiap rutenya. Tujuan penyelesaian MDVRPTW adalah mendapatkan rute optimal dengan total travel time terkecil dan tidak melebihi time windows-nya. Algoritma Particle Swarm Optimization (PSO) digunakan untuk menyelesaikan MDVRPTW. Cara kerja PSO diadaptasi dari perilaku sosial dari sekawanan burung dalam mencari makan. Algoritma ini bekerja dengan cara melakukan inisialisasi, mengevaluasi, mengonstruksi rute, dan memperbaharui rute hingga optimal. Penelitian diuji pada studi kasus pengambilan bahan baku suatu perusahaan dengan 2 depot penyimpanan dan 169 agen. Implementasi PSO berhasil membentuk rata-rata travel time setiap rute adalah 7,83 jam yang artinya time windows tidak dilanggar dan kapasitas kendaraan terpenuhi.]]>
