Genetic Algorithm and Particle Swarm Optimization on Fertilizer Production Planning Optimization

Abstract

Production planning is the important part of controlling the cost spent by the company. In this research, production planning model is linear integer programming model with constraints : production, worker, and inventory. Linear integer programming as optimization problem can be solved by exact method like branch and bound, cutting plane or heuristic method. In this paper, we use heurisitic like Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for solving production planning optimization in approaching. GA uses natural selection process of chromosomes while PSO is inspired by the behavior of flocks of birds, swarm of insects, or school of fish. The simulations show that both GA and PSO can find optimal solution of fertilizer production planning in approaching.