An application of genetic algorithm and PSO in an inventory model for a single deteriorating item with variable demand dependent on marketing strategy and displayed stock level

Abstract

This paper deals with an inventory model applied to a single deteriorating item considering the impact of marketing decisions and displaced stock level on the demand. Partial backlogged shortages are allowed. Different scenarios have been investigated through analyzing the shop storage capacity and demand parameters. For each scenario, the corresponding problem has been formulated as a nonlinear mixed integer optimization problem and solved by a real coded genetic algorithm and a particle swarm optimization technique. To illustrate the inventory model, a numerical example has been solved and sensitivity analyses have been done numerically to study the effect of changes of different parameters on the optimal policies.