Article ID: | iaor20123698 |
Volume: | 20 |
Issue: | 2 |
Start Page Number: | 251 |
End Page Number: | 280 |
Publication Date: | Jun 2012 |
Journal: | Central European Journal of Operations Research |
Authors: | Kar Samarjit, Roy Arindam, Das Debasis, Kar Mohuya |
Keywords: | simulation: analysis, heuristics: genetic algorithms, combinatorial optimization |
This paper develops a production‐inventory model for a deteriorating item with stock‐dependent demand under two storage facilities over a random planning horizon, which is assumed to follow exponential distribution with known parameter. The effects of learning in set‐up, production, selling and reduced selling is incorporated. Different inflation rates for various inventory costs and time value of money are also considered. A hybrid genetic algorithm is designed to solve the optimization problem which is hard to solve with existing algorithms due to the complexity of the decision variable. To illustrate the model and to show the effectiveness of the proposed approach a numerical example is provided. A sensitivity analysis of the optimal solution with respect to the parameters of the system is carried out.