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    Entropy-based multi-item solid transportation problems with uncertain variables
    (Springer Nature, 2019-07-01) Dalman, Hasan;
    This paper focuses on modeling and optimization of entropy-based uncertain multi-item solid transportation problems (MISTPs), in which direct costs, supplies, demands, conveyance capacities are uncertain nature. The purpose is to minimize the total uncertain cost via maximum entropy which ensures uniform delivery of products from sources to destinations through conveyances. The expected value programming and expected constrained programming models for optimizing the entropy-based uncertain MISTPs are constructed. These models are based on uncertainty theory. Subsequently, the constructed models are converted into their deterministic equivalences which are solved using two known mathematical programming methods. Finally, a numerical example is given to illustrate the models.
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    A fuzzy logic based approach to solve interval multiobjective nonlinear transportation problem
    (Springer Nature, 2019-06-01) Dalman, Hasan; Sivri, Mustafa
    This paper presents the solution procedure of multiobjective nonlinear transportation problem (MNOTP) where the cost coefficients of the objective functions, and the supply and the unknown demand parameters have been formulated as interval numbers by the decision maker. This problem has been converted into a conventional MNOTP where to minimize the interval nonlinear objective functions, the order relations that define the choice between intervals have been determined by the interval arithmetic. Also, the constraints with interval supply and unknown demand parameters have been transformed into its deterministic forms. Then the deterministic problems have been solved by two compromise programming methods. Finally, a numerical example is presented to illustrate the efficiency of the proposed procedure as well.
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    Interactive goal programming algorithm with Taylor series and interval type 2 fuzzy numbers
    (Springer Nature, 2019-06-01) Dalman, Hasan; Bayram, Mustafa
    This paper presents an interactive fuzzy goal programming (FGP) approach for solving Multiobjective Nonlinear Programming Problems (MONLPP) with interval type 2 fuzzy numbers (IT2 FNs). The cost and time of the objective functions, and the requirements of each kind of resources are taken to be trapezoidal IT2 FNs. Here, the considered fuzzy problem is first transformed into an equivalent crisp MONLPP, and then the MONLPP is converted into an equivalent multiobjective linear programming problem (MOLPP). By using an algorithm based on Taylor series, this problem is also reduced into a single objective linear programming problem (LPP) which can be easily solved by Maple 2017 optimization toolbox. Finally, the proposed solution procedure is illustrated by a numerical example.