Article ID: | iaor20135006 |
Volume: | 17 |
Issue: | 1 |
Start Page Number: | 22 |
End Page Number: | 45 |
Publication Date: | Nov 2014 |
Journal: | International Journal of Logistics Systems and Management |
Authors: | Paul Sanjoy Kumar, Azeem Abdullahil, Masud Md Abdulla Al |
Keywords: | quality & reliability, inventory, heuristics: genetic algorithms |
In this paper, a production inventory model with reliability of production process is developed to minimise total inventory cost. Production, setup, holding, inspection, depreciation, rejection and backorder cost are considered to develop the model. The economic production lot size and the reliability of the production process along with the production period are the decision variables and total cost per cycle is the objective function which is to be minimised. A meta‐heuristic particle swarm optimisation (PSO) algorithm is applied to solve the unconstrained non‐integer non‐linear form of objective function. Some numerical examples have been presented to explain the model. The results obtained from PSO algorithm are compared with results obtained from genetic algorithm (GA) applying on the same inventory model. Comparison clearly shows the superiority of PSO results over GA results thus makes PSO a better choice for this kind of modelling.