A novel solving method for multi-objective decision making problems under fuzzy conditions
محورهای موضوعی : Operation ResearchAlireza Alinezhad 1 , Abolfazl Kazemi 2 , Mojgan Khorasani 3
1 - Associate Professor, Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin branch, Islamic Azad University, Qazvin, Iran.
2 - Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
3 - Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
کلید واژه: goal programming, Multiple Objective Optimization, Relative Importance, Satisfying Optimization,
چکیده مقاله :
This paper proposes a satisfying optimization method for fuzzy multiple objective optimization problem. Actually, the presented method realizes the trade-off between optimization and fuzzy importance requirement. Generally, the main aim of the presented approach is to make the more important objective achieving the higher desirable satisfying degree. In practice, vagueness and imprecision of the goals, constraints and parameters in this problem make the decision-making complicated for decision makers who have to deal with the parameters to make the optimized decision. Hence, the reformulated optimization models based on goal programming is proposed for different fuzzy relations and fuzzy importance. In fact, decision makers can select the appropriate alternative considering their determinations from variety of solutions using parameter λ. Applying the proposed model, not only the satisfying results of all the objectives can be acquired, but also the fuzzy importance requirement can be simultaneously actualized. In addition, a numerical example is provided to illustrate how the model is applied. Finally, the conclusions and recommendations are presented.
This paper proposes a satisfying optimization method for fuzzy multiple objective optimization problem. Actually, the presented method realizes the trade-off between optimization and fuzzy importance requirement. Generally, the main aim of the presented approach is to make the more important objective achieving the higher desirable satisfying degree. In practice, vagueness and imprecision of the goals, constraints and parameters in this problem make the decision-making complicated for decision makers who have to deal with the parameters to make the optimized decision. Hence, the reformulated optimization models based on goal programming is proposed for different fuzzy relations and fuzzy importance. In fact, decision makers can select the appropriate alternative considering their determinations from variety of solutions using parameter λ. Applying the proposed model, not only the satisfying results of all the objectives can be acquired, but also the fuzzy importance requirement can be simultaneously actualized. In addition, a numerical example is provided to illustrate how the model is applied. Finally, the conclusions and recommendations are presented.
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