Evolutionary algorithm for inventory problem

This paper presents a new solution for solving continuous inventory problem in estimating the amount of purchase item and prediction on the maximization of profit in a restaurant. Particle swarm optimization (PSO) which has the ability of better convergence and efficiency is employed. The solution focuses on a single item in inventory list and single-buyer single-vendor relationship where demand presents as stochastic problem in a restaurant. Result and findings was compared with genetic algorithm (GA). Several testing were conducted to access the performance of each algorithm based on parameters and computational times. The finding demonstrates that these algorithms are competitive in solving this particular problem. The outcome is beneficial to the restaurant in terms of making decision on inventory and subsequently able to sustain the business.