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Hitoshi Yano - One of the best experts on this subject based on the ideXlab platform.

  • Interactive Decision Making with fuzzy goals for simple recourse in multiobjective stochastic programming problems
    International Journal of Multicriteria Decision Making, 2018
    Co-Authors: Hitoshi Yano, Ichiro Nishizaki, Rongrong Zhang
    Abstract:

    In this paper, we focus on multiobjective stochastic programming problems, and propose two Interactive fuzzy Decision-Making methods to obtain a satisfactory solution of a Decision maker. In the proposed methods, equality constraints with random variables are formulated on the basis of the two-stage programming method, in which two kinds of random variables, i.e., continuous ones and discrete ones, are considered, respectively. Under the assumption that the Decision maker has fuzzy goals not only for the original objective functions but also for the expectations of shortages and excesses for the violation of the equality constraints, the M-α-Pareto optimality concept is introduced, and two Interactive fuzzy Decision-Making methods are proposed to obtain a satisfactory solution from among an M-α-Pareto optimal solution set. The proposed method is applied to a farm planning problem in the Philippines, in which it is assumed that an amount supplied of water resource in dry season is represented as a continuous or discrete random variable.

  • Interactive Decision Making for Multiobjective Simple Recourse Programming Problems with Discrete or Continuous Fuzzy Random Variables
    Transactions on Engineering Technologies, 2017
    Co-Authors: Hitoshi Yano, Rongrong Zhang
    Abstract:

    In this paper, we formulate multiobjective simple recourse programming problems in which discrete fuzzy random variables or continuous ones are involved in equality constraints. In the proposed methods, equality constraints with two types of fuzzy random variables are defined on the basis of a possibility measure and and a two-stage programming method. For a given permissible possibility level specified by the Decision maker, a Pareto optimality concept is introduced. Both an Interactive linear programming algorithm for discrete fuzzy random variables and an Interactive convex programming algorithm for continuous fuzzy random variables are developed to obtain a satisfactory solution from among a Pareto optimal solution set. The proposed methods are applied to farm planning problems in the Philippines, in which it is assumed that the amount of water supply in dry season is represented as a discrete fuzzy random variable or a continuous one.

  • SCIS&ISIS - Interactive Decision Making for fuzzy random multiobjective linear programming problems with variance-covariance matrices through probability maximization
    The 6th International Conference on Soft Computing and Intelligent Systems and The 13th International Symposium on Advanced Intelligence Systems, 2012
    Co-Authors: Hitoshi Yano
    Abstract:

    In this paper, we focus on fuzzy random multiobjective linear programming problems with variance-covariance matrices through probability maximization, and propose an Interactive Decision Making method to obtain a satisfactory solution. In the proposed method, it is assumed that the Decision maker has fuzzy goals for not only permissible objective levels but also the corresponding distribution functions. Such fuzzy goals are quantified by eliciting the corresponding membership functions. Using the fuzzy Decision, such two kinds of membership functions are integrated, and D p -Pareto optimal solution concept is defined in the integrated membership space. By using the bisection method and the convex programming technique, the satisfactory solution is obtained from among a D p -Pareto optimal solution set through the interaction with the Decision maker.

  • MDAI - Interactive Decision Making for Hierarchical Multiobjective Linear Programming Problems
    Modeling Decisions for Artificial Intelligence, 2009
    Co-Authors: Hitoshi Yano
    Abstract:

    In this paper, we focus on hierarchical multiobjective linear programming problems where multiple Decision makers in a hierarchical organization have their own multiple objective linear functions together with common linear constraints, and propose an Interactive Decision Making method to obtain the satisfactory solution which reflects not only the hierarchical relationships between multiple Decision makers but also their own preferences for their objective functions. In the proposed method, instead of Pareto optimal concept, the generalized ***-extreme point concept is introduced. In order to obtain the satisfactory solution from among the generalized ***-extreme point set, an Interactive Decision Making method based on the linear programming is proposed, and an Interactive processes are demonstrated by means of an illustrative numerical example.

  • Interactive Decision Making for Multiobjective Fuzzy Linear Regression Analysis
    Multiple Criteria Decision Making, 1994
    Co-Authors: Masatoshi Sakawa, Hitoshi Yano
    Abstract:

    In this paper, to cope with the fuzzy environment where human subjective estimation is influential in the linear regression models, fuzzy linear regression models are introduced via the concepts of possibility and necessity. In fuzzy linear regression models, deviations between the observed values and the estimated values are assumed to be depending on the fuzziness of the parameters of the system. Given the fuzzy threshold for the three indices, three types of single-objective programming problems for obtaining fuzzy linear regression models, where input data is a vector of nonfuzzy numbers and output data is a fuzzy number, are formulated as natural extension of usual linear regression models. As an obvious advantage of these formulations, it is shown that all of the formulated problems can be reduced to linear programming ones. Moreover, by considering the conflict between the fuzzy threshold for the three indices and the fuzziness of the fuzzy linear regression model, the multiobjective programming problems for obtaining the fuzzy linear regression models are formulated, where both the fuzzy threshold and the fuzziness of the models are optimized corresponding to the three indices. Then on the basis of the linear programming method an Interactive Decision Making method to derive the satisficing solution for the Decision maker for the formulated multiobjective programming problems is developed. Finally, the proposed method is applied to the identification problem of the pork demand function to demonstrate its appropriateness and efficiency.

Hideki Katagiri - One of the best experts on this subject based on the ideXlab platform.

  • Interactive Decision Making for uncertain minimum spanning tree problems with total importance based on a risk-management approach
    Applied Mathematical Modelling, 2013
    Co-Authors: Takashi Hasuike, Hideki Katagiri
    Abstract:

    Abstract This paper deals with a minimum spanning tree problem where each edge cost includes uncertainty and importance measure. In risk management to avoid adverse impacts derived from uncertainty, a d -confidence interval for the total cost derived from robustness is introduced. Then, by maximizing the considerable region as well as minimizing the cost-importance ratio, a biobjective minimum spanning tree problem is proposed. Furthermore, in order to satisfy the objects of the Decision maker and to solve the proposed model in mathematical programming, fuzzy goals for the objects are introduced as satisfaction functions, and an exact solution algorithm is developed using Interactive Decision Making and deterministic equivalent transformations. Numerical examples are provided to compare our proposed model with some previous models.

  • SCIS&ISIS - Interactive Decision Making for random fuzzy two-level programming problems through probability-possibility maximization
    The 6th International Conference on Soft Computing and Intelligent Systems and The 13th International Symposium on Advanced Intelligence Systems, 2012
    Co-Authors: Shimpei Matsumoto, Kosuke Kato, Hideki Katagiri
    Abstract:

    In this paper, we propose an Interactive Decision Making algorithm for two-level linear programming problems under random and fuzzy environments. First we transform the original two-level programming problem with random fuzzy coefficients into a deterministic one on the basis of probability-possibility maximization. Then, we construct an Interactive algorithm to obtain a compromise solution for the Decision maker at the upper level in consideration of the cooperative relationship between Decision makers.

  • GrC - Interactive Decision Making for a shortest path problem with interval arc lengths
    2011 IEEE International Conference on Granular Computing, 2011
    Co-Authors: Takashi Hasuike, Hideki Katagiri
    Abstract:

    This paper considers a shortest path problem with interval costs for directed arcs and reliability for networks, and proposes a bi-objective interval shortest path problem. The proposed model is not well-defined due to interval costs, and so the deterministic constrained shortest path problem is obtained by introducing the order relation of interval values. In order to solve this bi-objective problem, a solution algorithm based on Interactive fuzzy satsificing method in terms of multi-objective programming is developed.

  • Interactive Decision Making USING POSSIBILITY AND NECESSITY MEASURES FOR A FUZZY RANDOM MULTIOBJECTIVE 0–1 PROGRAMMING PROBLEM
    Cybernetics and Systems, 2006
    Co-Authors: Hideki Katagiri, Masatoshi Sakawa, Ichiro Nishizaki
    Abstract:

    This article deals with a multiobjective 0–1 programming problem involving fuzzy random variable coefficients. A novel Decision-Making model based on stochastic programming and possibilistic programming is proposed. The aim of this article is to seek a solution to maximize expected degrees of possibility or necessity for which objective function values satisfy fuzzy goals. It is shown that the problem, including fuzziness and randoness, equivalently is transformed into a deterministic multiobjective stochastic 0–1 programming problem. In order to find a satisficing solution of the problem for a Decision maker, Interactive Decision Making is constructed using the reference point method.

Alan G. Sanfey - One of the best experts on this subject based on the ideXlab platform.

  • Predicting the other in cooperative interactions
    Trends in Cognitive Sciences, 2015
    Co-Authors: Alan G. Sanfey, Claudia Civai, Peter Vavra
    Abstract:

    Recent research has shown that a collection of neurons in dorsal anterior cingulate cortex of rhesus monkeys may specifically encode the choice selection of an interaction partner. This raises interesting and important questions as to the nature of Theory of Mind processes in social Interactive Decision-Making, with potential societal implications.

  • Interactive Decision-Making in people with schizotypal traits: A game theory approach
    Psychiatry Research-neuroimaging, 2010
    Co-Authors: Mascha Van 't Wout, Alan G. Sanfey
    Abstract:

    Studies that have investigated whether deficits in social cognition observed in schizophrenia are also present in schizotypal individuals have largely been inconclusive, and none of these studies have examined social Interactive behavior. Here, we investigated Interactive Decision-Making behavior in individuals differing in the amount of schizotypal symptoms using tasks derived from Game Theory. In total 1691 undergraduate students were screened with the Schizotypal Personality Questionnaire-Brief version. We selected 69 people distributed across the full schizotypal continuum to participate in Ultimatum and Dictator Games in which they played against human and non-human, computer partners. The results showed that higher levels of schizotypal symptoms, particularly positive and disorganized schizotypy, were related to proposing higher offers to all partners. Additionally, the amount of interpersonal schizotypal symptoms was associated with an increased acceptance rate of very unfair offers from human partners, possibly reflecting a blunted emotional response to such offers. We conclude that positive and disorganized schizotypal symptoms are associated with less adequate bargaining behavior, similar to what has been recently observed in patients with schizophrenia. The observed similarities on Ultimatum Game behavior between patients with schizophrenia and individuals with more schizotypal symptoms contribute to the growing evidence that social cognitive deficits may represent a marker of vulnerability to schizophrenia.

  • The Influence of Emotion Regulation on Social Interactive Decision-Making
    Emotion, 2010
    Co-Authors: Mascha Van 't Wout, Luke J. Chang, Alan G. Sanfey
    Abstract:

    Although adequate emotion regulation is considered to be essential in every day life, it is especially important in social interactions. However, the question as to what extent two different regulation strategies are effective in changing Decision-Making in a consequential socially Interactive context remains unanswered. We investigated the effect of expressive suppression and emotional reappraisal on strategic Decision-Making in a social Interactive task, that is, the Ultimatum Game. As hypothesized, participants in the emotional reappraisal condition accepted unfair offers more often than participants in the suppression and no-regulation condition. Additionally, the effect of emotional reappraisal influenced the amount of money participants proposed during a second interaction with partners that had treated them unfairly in a previous interaction. These results support and extend previous findings that emotional reappraisal as compared to expressive suppression, is a powerful regulation strategy that influences and changes how we interact with others even in the face of inequity.

Masatoshi Sakawa - One of the best experts on this subject based on the ideXlab platform.

  • Interactive Decision Making USING POSSIBILITY AND NECESSITY MEASURES FOR A FUZZY RANDOM MULTIOBJECTIVE 0–1 PROGRAMMING PROBLEM
    Cybernetics and Systems, 2006
    Co-Authors: Hideki Katagiri, Masatoshi Sakawa, Ichiro Nishizaki
    Abstract:

    This article deals with a multiobjective 0–1 programming problem involving fuzzy random variable coefficients. A novel Decision-Making model based on stochastic programming and possibilistic programming is proposed. The aim of this article is to seek a solution to maximize expected degrees of possibility or necessity for which objective function values satisfy fuzzy goals. It is shown that the problem, including fuzziness and randoness, equivalently is transformed into a deterministic multiobjective stochastic 0–1 programming problem. In order to find a satisficing solution of the problem for a Decision maker, Interactive Decision Making is constructed using the reference point method.

  • Interactive Decision Making for mulitobjective nonconvex programming problems with fuzzy numbers through coevolutionary genetic algorithms
    Fuzzy Sets and Systems, 2000
    Co-Authors: Masatoshi Sakawa, Katsuhiro Yauchi
    Abstract:

    Abstract In this paper, by considering the experts’ fuzzy understanding of the nature of the parameters in the problem-formulation process, multiobjective nonconvex nonlinear programming problems with fuzzy numbers are formulated. Using the level sets of fuzzy numbers, the corresponding nonfuzzy programming problems together with an extended Pareto optimality concept are introduced. For deriving a satisficing solution for the Decision maker from an extended Pareto optimal solution set, an Interactive Decision Making method is presented. In the proposed Interactive Decision Making method, if the Decision maker specifies the degree of the level sets of fuzzy numbers and the reference objective values, the corresponding extended Pareto optimal solution can be obtained by solving the augmented minimax problems for which the coevolutionary genetic algorithm, called GENOCOP III, is applicable. In order to overcome the drawbacks of GENOCOP III, the revised GENOCOP III is proposed by introducing a method for generating an initial feasible point and a bisection method for generating a new feasible point efficiently. Illustrative numerical examples demonstrate the feasibility and efficiency of the proposed method.

  • Interactive Decision-Making for multiobjective linear fractional programming problems with block angular structure involving fuzzy numbers
    Fuzzy Sets and Systems, 1998
    Co-Authors: Masatoshi Sakawa, Kosuke Kato
    Abstract:

    Abstract In this paper, by considering the experts' vague or fuzzy understanding of the nature of the parameters in the problem-formulation process, multiobjective linear fractional programming problems with block angular structure involving fuzzy numbers are formulated. Through the use of the α-level sets of fuzzy numbers, an extended Pareto optimality concept called the α-Pareto optimality is introduced. To generate a candidate for the satisficing solution which is also α-Pareto optimal, the Decision maker is asked to specify the degree α and the reference objective values. It is shown that the corresponding α-Pareto optimal solution can be easily obtained by solving the minimax problems for which the Dantzig-Wolfe decomposition method and Ritter's partitioning procedure are applicable. Then a linear programming-based Interactive Decision-Making method with decomposition procedures for deriving a satisficing solution for the Decision maker efficiently from an α-Pareto optimal solution set is presented. An illustrative numerical example is provided to demonstrate the feasibility of the proposed method.

  • Interactive Decision Making for large-scale multiobjective linear programs with fuzzy numbers
    Fuzzy Sets and Systems, 1997
    Co-Authors: Masatoshi Sakawa, Kosuke Kato
    Abstract:

    Abstract In this paper, by considering the experts' imprecise or fuzzy understanding of the nature of the parameters in the problem-formulation process, large-scale multiobjective block-angular linear programming problems involving fuzzy numbers are formulated. Through the use of the α-level sets of fuzzy numbers, an extended Pareto optimality concept, called the α-Pareto optimality is introduced. To generate a candidate for the satisficing solution which is also a-Pareto optimal, Decision maker is asked to specify the degree α and the reference objective values. It is shown that the corresponding α-Pareto optimal solution can be easily obtained by solving the minimax problems for which the Dantzig-Wolfe decomposition method is applicable. Then a linear programming-based Interactive Decision-Making method for deriving a satisficing solution for the Decision maker efficiently from an α-Pareto optimal solution set is presented.

  • Interactive Decision Making for Multiobjective Fuzzy Linear Regression Analysis
    Multiple Criteria Decision Making, 1994
    Co-Authors: Masatoshi Sakawa, Hitoshi Yano
    Abstract:

    In this paper, to cope with the fuzzy environment where human subjective estimation is influential in the linear regression models, fuzzy linear regression models are introduced via the concepts of possibility and necessity. In fuzzy linear regression models, deviations between the observed values and the estimated values are assumed to be depending on the fuzziness of the parameters of the system. Given the fuzzy threshold for the three indices, three types of single-objective programming problems for obtaining fuzzy linear regression models, where input data is a vector of nonfuzzy numbers and output data is a fuzzy number, are formulated as natural extension of usual linear regression models. As an obvious advantage of these formulations, it is shown that all of the formulated problems can be reduced to linear programming ones. Moreover, by considering the conflict between the fuzzy threshold for the three indices and the fuzziness of the fuzzy linear regression model, the multiobjective programming problems for obtaining the fuzzy linear regression models are formulated, where both the fuzzy threshold and the fuzziness of the models are optimized corresponding to the three indices. Then on the basis of the linear programming method an Interactive Decision Making method to derive the satisficing solution for the Decision maker for the formulated multiobjective programming problems is developed. Finally, the proposed method is applied to the identification problem of the pork demand function to demonstrate its appropriateness and efficiency.

Mark Lorenzen - One of the best experts on this subject based on the ideXlab platform.

  • towards an understanding of cognitive coordination theoretical developments and empirical illustrations
    Organization Studies, 2009
    Co-Authors: Nicolai Juul Foss, Mark Lorenzen
    Abstract:

    The cognitive dimension of institutions has been comparatively neglected in social science research. In particular, economists have concentrated on how institutions provide incentives. However, institutions also influence behaviours by influencing beliefs and expectations that help agents to overcome coordination problems. We explore various aspects of how institutions may align agents’ beliefs, concentrating on the role of analogies in Interactive Decision Making, and how analogies grow from experience. We illustrate our reasoning by an empirical example.