Developing a multi-objective, multi-item inventory model and three algorithms for its solution

Ommolbanin YOUSEFI; Mirbahadorgholi ARYANEZHAD; Seyed Jafar SADJADI; Arash SHAHIN

doi:10.1631/jzus.C1100384

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Developing a multi-objective, multi-item inventory model and three algorithms for its solution

计算机与自动化 | Updated：2022-12-09

- Developing a multi-objective, multi-item inventory model and three algorithms for its solution
- Developing a multi-objective, multi-item inventory model and three algorithms for its solution
- 信息与电子工程前沿（英文） 2012年13卷第8期页码：601-612
- Affiliations：
  
  1.Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
  2.Department of Management, University of Isfahan, Isfahan, Iran
- Author bio：
  
  [ "Ommolbanin YOUSEFI, E-mail: oyousefi@iust.ac.ir" ]
- Funds：
- DOI：10.1631/jzus.C1100384
  中图分类号： TP301.6
- 收稿：2012-12-28，
  
  修回：2012-;7-;6，
  
  纸质出版：2012-08
- Accepted：
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Developing a multi-objective, multi-item inventory model and three algorithms for its solution[J]. 信息与电子工程前沿（英文）, 2012,13(8):601-612.

Ommolbanin YOUSEFI, Mirbahadorgholi ARYANEZHAD, Seyed Jafar SADJADI, et al. Developing a multi-objective, multi-item inventory model and three algorithms for its solution[J]. Frontiers of Information Technology & Electronic Engineering, 2012, 13(8): 601-612.
Developing a multi-objective, multi-item inventory model and three algorithms for its solution[J]. 信息与电子工程前沿（英文）, 2012,13(8):601-612. DOI： 10.1631/jzus.C1100384.

Ommolbanin YOUSEFI, Mirbahadorgholi ARYANEZHAD, Seyed Jafar SADJADI, et al. Developing a multi-objective, multi-item inventory model and three algorithms for its solution[J]. Frontiers of Information Technology & Electronic Engineering, 2012, 13(8): 601-612. DOI： 10.1631/jzus.C1100384.

摘要

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.

关键词

Keywords

references

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