Modelling of Multi-Objective Transshipment Problem with Fuzzy Goal Programming

被引:2
|
作者
Alp, Selcuk [1 ]
Ozkan, Tugba Kiral [2 ]
机构
[1] Yildiz Tech Univ, Dept Ind Engn, Istanbul, Turkey
[2] Bahcesehir Univ, Fac Educ Sci, Istanbul, Turkey
来源
INTERNATIONAL JOURNAL OF TRANSPORTATION | 2018年 / 6卷 / 02期
关键词
Fuzzy Goal programming; Transshipment Problem;
D O I
10.14257/ijt.2018.6.2.02
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
The purpose of the transportation problem is trying to find the best route to meet the demands by using the supply points with capacity. While the Transportation problem only allowed products to be conveyed directly from the supply centers to demand centers, problem of transshipment transfer centers are also used. Linear programming methods can be used to solve the transportation problems. However, in the presence of numerical targets to achieve; Goal programming method is used instead of Linear Programming. Goal programming is a method applied to linear programming problems with a large number of goals and objectives. On the contrary to linear programming methods which is optimizing an objective; goal programming, used to deliver results for conflicting objectives by minimizing the deviation between objective values and the realized results. Fuzzy Goal Programming approach is used to solve problems if the exact value is not measured for the objectives and constraints. The purpose of this article is to put forth that the fuzzy goal programming which we can accept as one of the best decision-making models that can be used under the fuzzy and reveal the solution, can be used for the modeling of a transshipment problem.
引用
收藏
页码:9 / 20
页数:12
相关论文
共 50 条
  • [31] A multi-objective genetic algorithm for solving cell formation problem using a fuzzy goal programming approach
    Saeidi, S. (sh_saeidi@iaut.ac.ir), 1635, Springer London (70): : 9 - 12
  • [32] Goal programming tactic for uncertain multi-objective transportation problem using fuzzy linear membership function
    Uddin, Md. Sharif
    Miah, Musa
    Khan, Md. Al-Amin
    AlArjani, Ali
    ALEXANDRIA ENGINEERING JOURNAL, 2021, 60 (02) : 2525 - 2533
  • [33] A multi-objective genetic algorithm for solving cell formation problem using a fuzzy goal programming approach
    Saeidi, Shahram
    Solimanpur, Maghsud
    Mahdavi, Iraj
    Javadian, Nikbakhsh
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2014, 70 (9-12): : 1635 - 1652
  • [34] A multi-objective genetic algorithm for solving cell formation problem using a fuzzy goal programming approach
    Shahram Saeidi
    Maghsud Solimanpur
    Iraj Mahdavi
    Nikbakhsh Javadian
    The International Journal of Advanced Manufacturing Technology, 2014, 70 : 1635 - 1652
  • [35] On a generalized fuzzy goal optimization for solving fuzzy multi-objective linear programming problems
    Faculty of Information Technology, University of Technology, Sydney, PO Box 123, Broadway, NSW 2007, Australia
    J. Intelligent Fuzzy Syst., 2007, 1 (83-97):
  • [36] On a generalized fuzzy goal optimization for solving fuzzy multi-objective linear programming problems
    Lu, Jie
    Wu, Fengjie
    Zhang, Guangquan
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2007, 18 (01) : 83 - 97
  • [37] Multi-objective university rescheduling problem by fuzzy programming technique
    Bhoi, Sunil B.
    Dhodiya, Jayesh M.
    EUROPEAN JOURNAL OF INDUSTRIAL ENGINEERING, 2024, 18 (06) : 885 - 909
  • [38] Multi-objective Linear Fractional Programming Problem with Fuzzy Parameters
    Nayak, Suvasis
    Ojha, Akshay Kumar
    SOFT COMPUTING FOR PROBLEM SOLVING, SOCPROS 2017, VOL 1, 2019, 816 : 79 - 90
  • [39] Fuzzy Random Possibilistic Programming Model for Multi-objective Problem
    Nureize, A.
    Watada, J.
    2012 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT (IEEM), 2012, : 2204 - 2208
  • [40] Fuzzy Programming Approach to Solve Multi-objective Transportation Problem
    Kumar, Sandeep
    Pandey, Diwakar
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON SOFT COMPUTING FOR PROBLEM SOLVING (SOCPROS 2011), VOL 1, 2012, 130 : 525 - 533