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THE METHOD OF SUPPORTING DECISIONS UNDER RISK BASED ON MULTIOBJECTIVE OPTIMIZATION

100%
Łodziński A.
Metody Ilościowe w Badaniach Ekonomicznych
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2013
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vol. 14
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issue 2
39-50
EN
The method of supporting decisions under risk was presented in this paper. Making decision under risk takes place when a result of a given decision is not explicit and depends on the condition of the environment. A decision-making process based on multiobjective optimization has been presented in this paper. Methods of multiobjective optimization do not give one unique solution, but a whole set of them. A decision making relies on interactive conducting of the decision making process. Selection of given decision is made by way of solving a problem with parameters defining aspirations of a decision maker and the evaluation of obtained results. A decision maker defines a parameter, for which a solution is indicated. Then he or she evaluates the received solution by either accepting or rejecting it. In the second case a decision maker provides a new parameter value and a problem is solved again for the new parameter.39-50
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Neutrosophic compromise programming approach for multiobjective nonlinear transportation problem with supply and demand following the exponential distribution

88%
ADHAMI A. Y., FAIZAN M., M A.
Operations Research and Decisions
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2022
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vol. 32
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issue 3
1-15
EN
Decision-making is a tedious and complex process. In the present competitive scenario, any incorrect decision may excessively harm an organization. Therefore, the parameters involved in the decision-making process should be looked into carefully as they may not always be of a deterministic nature. In the present study, a multiobjective nonlinear transportation problem is formulated, wherein the parameters involved in the objective functions are assumed to be fuzzy and both supply and demand are stochastic. Supply and demand are assumed to follow the exponential distribution. After converting the problem into an equivalent deterministic form, the multiobjective problem is solved using a neutrosophic compromise programming approach. A comparative study indicates that the proposed approach provides the best compromise solution, which is significantly better than the one obtained using the fuzzy programming approach.
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