Neutrosophic set theory plays an important role in dealing with the impreciseness and inconsistency in data encountered in solving real life problems. This article aims to present a novel goal programming based strate...
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Neutrosophic set theory plays an important role in dealing with the impreciseness and inconsistency in data encountered in solving real life problems. This article aims to present a novel goal programming based strategy which will be helpful to solve multi-levelmulti-objective Linear programming Problem (MLMOLPP) with parameters as neutrosophic numbers (NNs). Difficulty in decision making arises due to the presence of multiple decision makers (DMs) and impreciseness in information. Here each level DM has multiple linear objective functions with parameters considered as NNs which are represented in the formc+dI wherecanddare considered real numbers and the symbolIdenotes indeterminacy. The constraints are also linear with the parameters as NNs. Firstly the NNs are changed into intervals and the problem turns into a multi-levelmulti-objective linear programming problem considering interval parameters. Then interval programming technique is employed to obtain the target interval of each objective function. In order to avoid decision deadlock which may arise in hierarchical (multi-level) problem, a possible relaxation is imposed by each level DM on the decision variables under his/her control. Finally a goal programming strategy is presented to solve the MLMOLPP with interval parameters. The method presented in this paper facilitates to solve MLMOLPP with multiple conflicting objectives in an uncertain environment represented through NNs of the formc+dI where indeterminacyIplays a pivotal role. Lastly, a mathematical example is solved to show the novelty and applicability of the developed strategy.
The aim of this paper is to propose an algorithm to solve and enhance a multi-levelmulti-objective integer quadratic programming problem (MLMOIQPP) under a single-valued Pentagonal Neutrosophic environment applied to...
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The aim of this paper is to propose an algorithm to solve and enhance a multi-levelmulti-objective integer quadratic programming problem (MLMOIQPP) under a single-valued Pentagonal Neutrosophic environment applied to the objective functions. The suggested solution takes advantage of multi-objective optimization in addition to the fuzzy approach as well as the branch and bound technique, which is implemented at each decision level to develop a generalized maximization-minimization model for obtaining the integer satisfactory solution after applying the score and accuracy function in the first phase of the solution methodology to singlevalued Pentagonal Neutrosophic parameters to be converted into an equal crisp form. An illustrative example is demonstrated to validate the proposed solution algorithm.
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