Fuzzy programming with hyperbolic membership functions for multiobjective capacitated transportation problem

OPSEARCH ◽  
2004 ◽  
Vol 41 (2) ◽  
pp. 106-120
Author(s):  
A. K. Bit
Keyword(s):  
Transportation Problem ◽  
Fuzzy Programming ◽  
Membership Functions ◽  
Capacitated Transportation Problem

scholarly journals A Compensatory Approach to Multiobjective Linear Transportation Problem with Fuzzy Cost Coefficients

2011 ◽  
Vol 2011 ◽  
pp. 1-19 ◽  
Author(s):  
Hale Gonce Kocken ◽  
Mehmet Ahlatcioglu
Keyword(s):  
Transportation Problem ◽  
Fuzzy Programming ◽  
Solution Procedure ◽  
Decision Making Process ◽  
Pareto Optimal ◽  
Objective Functions ◽  
Programming Technique ◽  
Nonlinear Structure ◽  
Multiobjective Approach ◽  
Fuzzy Cost

This paper deals with the Multiobjective Linear Transportation Problem that has fuzzy cost coefficients. In the solution procedure, many objectives may conflict with each other; therefore decision-making process becomes complicated. And also due to the fuzziness in the costs, this problem has a nonlinear structure. In this paper, fuzziness in the objective functions is handled with a fuzzy programming technique in the sense of multiobjective approach. And then we present a compensatory approach to solve Multiobjective Linear Transportation Problem with fuzzy cost coefficients by using Werner's operator. Our approach generates compromise solutions which are both compensatory and Pareto optimal. A numerical example has been provided to illustrate the problem.

scholarly journals Enhancement of Capacitated Transportation Problem in Fuzzy Environment

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Hamiden Abd El-Wahed Khalifa ◽  
Pavan Kumar ◽  
Majed G. Alharbi
Keyword(s):  
Objective Function ◽  
Transportation Problem ◽  
Research Work ◽  
Policy Makers ◽  
Suggested Approach ◽  
Penalty Cost ◽  
Fuzzy Environment ◽  
Order Relations ◽  
Capacitated Transportation Problem ◽  
Interval Linear

This research work aims to study a capacitated transportation problem (CTP) with penalty cost, supplies, and demands represented by hexagonal fuzzy numbers. Based on ranking function, the supplies and demands are converted to the crisp form. Through the use of the α‐level, the problem is converted into interval linear programming. To optimize the interval objective function, we define the order relations represented by policy maker’s choice between intervals. The maximization (minimization) problem considering the interval objective function is transformed to multiobjective optimization problem based on order relations introduced by the preference of policy makers between interval profits (costs). A numerical example is given for illustration and to check the validity of the suggested approach.

Sign in / Sign up

Export Citation Format

Share Document