Optimizing a bi-objective multi-product EPQ model with defective items,rework and limited orders: NSGA-II and MOPSO algorithms |
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Authors: | Seyed Hamid Reza Pasandideh Seyed Taghi Akhavan Niaki Sharareh Sharafzadeh |
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Affiliation: | 1. Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran;2. Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran;3. Faculty of Industrial and Mechanical Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran |
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Abstract: | In this paper, a bi-objective multi-products economic production quantity (EPQ) model is developed, in which the number of orders is limited and imperfect items that are re-workable are produced. The objectives of the problem are minimization of the total inventory costs as well as minimizing the required warehouse space. The model is shown to be of a bi-objective nonlinear programming type, and in order to solve it two meta-heuristic algorithms namely, the non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO) algorithm, are proposed. To verify the solution obtained and to evaluate the performance of proposed algorithms, two-sample t-tests are employed to compare the means of the first objective value, the means of the second objective values, and the mean required CPU time of solving the problem using two algorithms. The results show while both algorithms are efficient to solve the model and the solution qualities of the two algorithms do not differ significantly, the computational CPU time of MOPSO is considerably lower than that of NSGA-II. |
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Keywords: | Multi-product EPQ Multi-objective model Imperfect items Re-workable items NSGA-II MOPSO |
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