
<abstract> <p>Considering the uncertainty of transporting goods from numerous origins to diverse destinations is a critical task for the decision-maker (DM). The ultimate goal of the DM is to make the right decisions that optimize the profit or loss of the organization under the vagueness of the uncontrollable effects. In this paper, mathematical models are proposed using fuzzy non-linear membership functions for the transportation problem considering the parameters' uncertainty that can help the DM to optimize the multi-objective transportation problems (MOTP) and to achieve the desired goals by choosing a confidence level of the uncertain parameters. Based on DM's selection of the confidence level, a compromise solution of the uncertain multi-objective transportation (UMOTP) is obtained along with the satisfaction level in percent for the DM. Two non-linear fuzzy membership functions are considered: the exponential and the hyperbolic functions. Using both membership functions, the sensitivity analysis was implemented by considering different confidence levels. According to the experimental results, the hyperbolic membership function gives 100% DM's satisfaction in many instances. Moreover, it shows stability against the exponential and linear functions.</p> </abstract>
Statistics and Probability, Optimization, non-linear fuzzy-membership functions, Artificial intelligence, Social Sciences, Fuzzy Differential Equations and Uncertainty Modeling, Group Decision Making, Multi-Criteria Decision Making, Management Science and Operations Research, Multi-Objective Transportation Problem Optimization, Decision Sciences, Engineering, Fuzzy Goal Programming, Linear programming, compromise solution, QA1-939, FOS: Mathematics, Multi-Objective Optimization, Electronic engineering, Mathematical optimization, Membership function, Computer science, Sensitivity (control systems), Fuzzy Differential Equations, Fuzzy logic, transportation problem, Control and Systems Engineering, Vagueness, Physical Sciences, fuzzy multi-objective optimization, Fuzzy set, linear programming problem, Mathematics
Statistics and Probability, Optimization, non-linear fuzzy-membership functions, Artificial intelligence, Social Sciences, Fuzzy Differential Equations and Uncertainty Modeling, Group Decision Making, Multi-Criteria Decision Making, Management Science and Operations Research, Multi-Objective Transportation Problem Optimization, Decision Sciences, Engineering, Fuzzy Goal Programming, Linear programming, compromise solution, QA1-939, FOS: Mathematics, Multi-Objective Optimization, Electronic engineering, Mathematical optimization, Membership function, Computer science, Sensitivity (control systems), Fuzzy Differential Equations, Fuzzy logic, transportation problem, Control and Systems Engineering, Vagueness, Physical Sciences, fuzzy multi-objective optimization, Fuzzy set, linear programming problem, Mathematics
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