Optimasi Biaya Distribusi pada HFVRP Menggunakan Algoritma Particle Swarm Optimization

Distribution systems play a significant role in logistics operations. For the companies with consumer goods products this even more important as consumer goods production has fairly cheap price compared to the distribution cost that must be spent by the company. In addition, increased fuel costs have urged the company to be more efficient in planning and schedule the transportation routes. This paper presents the application of the Particle Swarm Optimization (PSO) algorithm to minimize the travel distance and total cost of a Heterogeneous Fleet Vehicle Routing Problem (HFVRP). Experimental results from its application to a real-world case study are presented. The model in this research is the HFVRP where vehicles have different capacities, variable costs, and fixed costs. PSO algorithm was applied because of the high number of customers served, and therefore the exact methods may not be sufficient. PSO parameter setting which produced the optimum result was with the number of swarms 50, C1 1,5, and C2 2 determined through the design of the experiment. The results of computation show that using PSO can minimize the total traveled distance with an average savings of 51.55% and minimize total cost with an average savings of 44.92% from the existing vehicle routes operated by the company.Distribution systems play a significant role in logistics operations. For the companies with consumer goods products this even more important as consumer goods production has fairly cheap price compared to the distribution cost that must be spent by the company. In addition, increased fuel costs have urged the company to be more efficient in planning and schedule the transportation routes. This paper presents the application of the Particle Swarm Optimization (PSO) algorithm to minimize the travel distance and total cost of a Heterogeneous Fleet Vehicle Routing Problem (HFVRP). Experimental results from its application to a real-world case study are presented. The model in this research is the HFVRP where vehicles have different capacities, variable costs, and fixed costs. PSO algorithm was applied because of the high number of customers served, and therefore the exact methods may not be sufficient. PSO parameter setting which produced the optimum result was with the number of swarms 50, C1 1,5, and C2 2 determined through the design of the experiment. The results of computation show that using PSO can minimize the total traveled distance with an average savings of 51.55% and minimize total cost with an average savings of 44.92% from the existing vehicle routes operated by the company