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Front. Inform. Technol. Electron. Eng.  2012, Vol. 13 Issue (8): 601-612    DOI: 10.1631/jzus.C1100384
    
Developing a multi-objective, multi-item inventory model and three algorithms for its solution
Ommolbanin Yousefi, Mirbahadorgholi Aryanezhad, Seyed Jafar Sadjadi, Arash Shahin
Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran; Department of Management, University of Isfahan, Isfahan, Iran
Developing a multi-objective, multi-item inventory model and three algorithms for its solution
Ommolbanin Yousefi, Mirbahadorgholi Aryanezhad, Seyed Jafar Sadjadi, Arash Shahin
Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran; Department of Management, University of Isfahan, Isfahan, Iran
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摘要： We develop a multi-objective model in a multi-product inventory system. The proposed model is a joint replenishment problem (JRP) that has two objective functions. The first one is minimization of total ordering and inventory holding costs, which is the same objective function as the classic JRP. To increase the applicability of the proposed model, we suppose that transportation cost is independent of time, is not a part of holding cost, and is calculated based on the maximum of stored inventory, as is the case in many real inventory problems. Thus, the second objective function is minimization of total transportation cost. To solve this problem three efficient algorithms are proposed. First, the RAND algorithm, called the best heuristic algorithm for solving the JRP, is modified to be applicable for the proposed problem. A multi-objective genetic algorithm (MOGA) is developed as the second algorithm to solve the problem. Finally, the model is solved by a new algorithm that is a combination of the RAND algorithm and MOGA. The performances of these algorithms are then compared with those of the previous approaches and with each other, and the findings imply their ability in finding Pareto optimal solutions to 3200 randomly produced problems.
关键词： Joint replenishment problem;  Multi-objective genetic algorithm;  RAND algorithm    
Abstract: We develop a multi-objective model in a multi-product inventory system. The proposed model is a joint replenishment problem (JRP) that has two objective functions. The first one is minimization of total ordering and inventory holding costs, which is the same objective function as the classic JRP. To increase the applicability of the proposed model, we suppose that transportation cost is independent of time, is not a part of holding cost, and is calculated based on the maximum of stored inventory, as is the case in many real inventory problems. Thus, the second objective function is minimization of total transportation cost. To solve this problem three efficient algorithms are proposed. First, the RAND algorithm, called the best heuristic algorithm for solving the JRP, is modified to be applicable for the proposed problem. A multi-objective genetic algorithm (MOGA) is developed as the second algorithm to solve the problem. Finally, the model is solved by a new algorithm that is a combination of the RAND algorithm and MOGA. The performances of these algorithms are then compared with those of the previous approaches and with each other, and the findings imply their ability in finding Pareto optimal solutions to 3200 randomly produced problems.
Key words: Joint replenishment problem    Multi-objective genetic algorithm    RAND algorithm
收稿日期: 2011-12-28 出版日期: 2012-08-02
CLC:  TP301.6  
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Ommolbanin Yousefi
Mirbahadorgholi Aryanezhad
Seyed Jafar Sadjadi
Arash Shahin

引用本文:

Ommolbanin Yousefi, Mirbahadorgholi Aryanezhad, Seyed Jafar Sadjadi, Arash Shahin. Developing a multi-objective, multi-item inventory model and three algorithms for its solution. Front. Inform. Technol. Electron. Eng., 2012, 13(8): 601-612.

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http://www.zjujournals.com/xueshu/fitee/CN/10.1631/jzus.C1100384    或    http://www.zjujournals.com/xueshu/fitee/CN/Y2012/V13/I8/601

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