Designing a New Particle Swarm Optimization for Make-with-Buy Inventory Model

In real world, some manufacturing companies may encounter the production restriction. For instance, if the number of products increases, given company may not be able to produce all products. Therefore, it may encounter the backlogging. On the other hand, if product demand increases, given company may encounter restricted capacity to respond to such demands; so, it will also encounter backlogging. In this paper, we consider such companies that will encounter the mentioned conditions. To respond these exceeded demands, companies will be enforced to buy some products from outside. Therefore, the objective of this paper is to determine the optimum quantities of make and buy for each product by minimizing total inventory cost. We refer to the proposed model as make-with-buy model. In this paper we formulate the make-with-buy model and solve it by two meta-heuristic algorithms namely genetic algorithm (GA) and particle swarm optimization (PSO).