H
Hitoshi Yano
Researcher at Women's College, Kolkata
Publications - 13
Citations - 531
Hitoshi Yano is an academic researcher from Women's College, Kolkata. The author has contributed to research in topics: Fuzzy logic & Fuzzy number. The author has an hindex of 8, co-authored 13 publications receiving 527 citations.
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Journal ArticleDOI
Multiobjective fuzzy linear regression analysis for fuzzy input-output data
Masatoshi Sakawa,Hitoshi Yano +1 more
TL;DR: In this article, three types of multiobjective programming problems for obtaining fuzzy linear regression models are formulated corresponding to the three indices, and a linear programming based interactive decision-making method is developed to derive the satisficing solution of the decision maker for the formulated multiobjectives programming problems.
Journal Article
Multiobjective fuzzy linear regression analysis for fuzzy input-output data
Masatoshi Sakawa,Hitoshi Yano +1 more
TL;DR: A linear programming based interactive decision making method to derive the satisficing solution of the decision maker for the formulated multiobjective programming problems is developed.
Journal ArticleDOI
Fuzzy linear regression analysis for fuzzy input-output data
Masatoshi Sakawa,Hitoshi Yano +1 more
TL;DR: A class of fuzzy linear regression models, where both input data and output data are fuzzy numbers, is introduced by using the three indices for equalities between fuzzy numbers using linear programming based methods for solving the formulated problems.
Journal ArticleDOI
A fuzzy dual decomposition method for large-scale multiobjective nonlinear programming problems
Masatoshi Sakawa,Hitoshi Yano +1 more
TL;DR: A fuzzy dual decomposition method for large-scale multiobjective nonlinear programming problems (LS-MONLPs) with the block angular structure by considering the vague nature of human judgements is proposed.
Journal ArticleDOI
Pareto optimality for multiobjective linear fractional programming problems with fuzzy parameters
TL;DR: Using the four indices for ranking two fuzzy numbers, four types of Pareto optimality are defined, and the relationships among them are examined in detail.