Distribution Cost Optimization Using Pigeon Inspired Optimization Method with Reverse Learning Mechanism

Abstract

Abstract The goal of this research was to optimize the cost of goods distribution to some locations. The problem can be considered as Vehicle Routing Problem (VRP). The main characteristic of this problem is that the solution space expands exponentially. In our case at hand, the goods distribution that have been done, mostly done manually. Therefore, it may not optimize the costs of distribution. Manual optimization cannot be used if the number is locations is more than five because the solution space is too big to solve by hand. Pigeon Inspired Optimization (PIO) is proposed as a heuristic method for optimizing the VRP to optimize the cost and then it will be compared with Particle Swarm Optimization (PSO) method as comparison algorithm. Evaluation was conducted by comparing their performance in optimizing cost for several solution spaces. The achieved result is the shortest distribution path according to the constraints given and has lowest total cost of distribution. It can be concluded that PIO is better for optimizing the goods distribution path so that the distribution cost becomes minimal.