A new approach for solving fully intuitionistic fuzzy transportation problems


          

刊名：Fuzzy Optimization and Decision Making: A Journal of Modeling and Computation Under Uncertainty
作者：Ebrahimnejad, Ali（Islamic Azad Univ, Qaemshahr Branch, Dept Math, Qaemshahr, Iran）
Luis Verdegay, Jose（Univ Granada, Dept Comp Sci & AI, E-18014 Granada, Spain）
刊号：519LB020
ISSN：1568-4539
出版年：2018
年卷期：2018, vol.17, no.4
页码：447-474
总页数：28
分类号：O22
关键词：Intuitionistic fuzzy transportation problem；Trapezoidal intuitionistic fuzzy number；Accuracy function
参考中译：
语种：eng
文摘：In this paper, a well-known network-structured problem called the transportation problem (TP) is considered in an uncertain environment. The transportation costs, supply and demand are represented by trapezoidal intuitionistic fuzzy numbers (TrIFNs) which are the more generalized form of trapezoidal fuzzy numbers involving a degree of acceptance and a degree of rejection. We formulate the intuitionistic fuzzy TP (IFTP) and propose a solution approach to solve the problem. The IFTP is converted into a deterministic linear programming (LP) problem, which is solved using standard LP algorithms. The main contributions of this paper are fivefold: (1) we convert the formulated IFTP into a deterministic classical LP problem based on ordering of TrIFNs using accuracy function; (2) in contrast to most existing approaches, which provide a crisp solution, we propose a new approach that provides an intuitionistic fuzzy optimal solution; (3) in contrast to existing methods that include negative parts in the obtained intuitionistic fuzzy optimal solution and intuitionistic fuzzy optimal cost, we propose a new method that provides non-negative intuitionistic fuzzy optimal solution and optimal cost; (4) we discuss about the advantages of the proposed method over the existing methods for solving IFTPs; (5) we demonstrate the feasibility and richness of the obtained solutions in the context of two application examples.



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