Browsing by Author "Tkacenko, Alexandra"

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FUZZY MULTICRITERIAL OPTIMIZATIONS IN THE TRANSPORTATION PROBLEM
(CEP USM, 2017) Tkacenko, Alexandra
In the paper an iterative fuzzy programming approach for solving the multi-objective transportation problem of ”bottleneck”type with some imprecise data is developed. Minimizing the worst upper bound to obtain an efficient solution which is close to the best lower bound for each objective function iterative, we find the set of efficient solutions for all time levels.
ITERATIVE APPROACH FOR SOLVING FUZZY MULTI-CRITERIA TRANSPORTATION PROBLEM OF "BOTTLENECK" TYPE
(Valines SRL, 2014) Tkacenko, Alexandra
In the paper an iterative fuzzy programming approach is developed for solving the multi-objective transportation problem of "bottleneck" type with some imprecise data. Minimizing iteratively the worst upper bound to obtain an e±cient solution which is close to the best lower bound for each objective function, we find the set of efficient solutions for all time levels.
THE METHOD FOR SOLVING THE MULTI-CRITERIA LINEAR-FRACTIONAL OPTIMIZATION PROBLEM IN INTEGERS
(2023) Tkacenko, Alexandra
In the paperwe propose a method for solving the linear-fractional multi-criteria optimization model with identical denominators in whole numbers. Such models are in increasing demand, especially from an application point of view. The solving procedure of these models initially involves assigning utilities (weights) to each criterion [15] and building the optimization model with a single criterion, which is a synthetic function of all criteria weighted. It was found that the optimal solution of the model does not depend on the values optimum of the criteria obtained in ?+ or in ?+. So, the decision maker can combinatorially select the types of optimal values of criteria, a fact that represents the essential priority of the algorithm. By changing the utility values, at the decision maker’s discretion, we will obtain a new optimal compromise solution of the model. Theoretical justification of the algorithm as well as a solved example are brought to work.
The Synthesis Function Method for Solving the Multi-Criteria Linear-Fractional Model in Integers [Articol]
(2024) Tkacenko, Alexandra
In this paper, I will propose a method for solving the linearfractional multi-criteria optimization model with identical denominators in whole numbers. The solving procedure involves assigning utilities (weights) to each criterion, after which a singlecriterion linear-fractional optimization model is constructed and can be solved. By changing the utility values, we can determine a new optimal compromise solution(s). The algorithm is theoretically justified and it was tested successfully on several examples.