A multi-objective mathematical programming problem with fuzzy relation constraints

1995 ◽  
Vol 4 (1) ◽  
pp. 23-35 ◽  
Author(s):  
Hsiao-Fan Wang
2012 ◽  
Vol 2012 ◽  
pp. 1-14
Author(s):  
Min Jiang ◽  
Zhiqing Meng ◽  
Xinsheng Xu ◽  
Rui Shen ◽  
Gengui Zhou

This paper extends an existing cooperative multi-objective interaction programming problem with interaction constraint for two players (or two agents). First, we define ans-optimal joint solution with weight vector to multi-objective interaction programming problem with interaction constraint for two players and get some properties of it. It is proved that thes-optimal joint solution with weight vector to the multi-objective interaction programming problem can be obtained by solving a corresponding mathematical programming problem. Then, we define anothers-optimal joint solution with weight value to multi-objective interaction programming problem with interaction constraint for two players and get some of its properties. It is proved that thes-optimal joint solution with weight vector to multi-objective interaction programming problem can be obtained by solving a corresponding mathematical programming problem. Finally, we build a pricing multi-objective interaction programming model for a bi-level supply chain. Numerical results show that the interaction programming pricing model is better than Stackelberg pricing model and the joint pricing model.


2019 ◽  
Vol 24 (3) ◽  
pp. 385-403
Author(s):  
Srikumar Acharya ◽  
Berhanu Belay ◽  
Rajashree Mishra

The paper presents the solution methodology of a multi-objective probabilistic fractional programming problem, where the parameters of the right hand side constraints follow Cauchy distribution. The proposed mathematical model can not be solved directly. The solution procedure is completed in three steps. In first step, multi-objective probabilistic fractional programming problem is converted to deterministic multi-objective fractional mathematical programming problem. In the second step, it is converted to its equivalent multi-objective mathematical programming problem. Finally, ε -constraint method is applied to find the best compromise solution. A numerical example and application are presented to demonstrate the procedure of proposed mathematical model.


2019 ◽  
Vol 29 (3) ◽  
pp. 337-358 ◽  
Author(s):  
Mitali Acharya ◽  
Adane Gessesse ◽  
Rajashree Mishra ◽  
Srikumar Acharya

In this paper, we considered a multi-objective stochastic transportation problem where the supply and demand parameters follow extreme value distribution having three-parameters. The proposed mathematical model for stochastic transportation problem cannot be solved directly by mathematical approaches. Therefore, we converted it to an equivalent deterministic multi-objective mathematical programming problem. For solving the deterministic multi-objective mathematical programming problem, we used an ?-constraint method. A case study is provided to illustrate the methodology.


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