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Fuzzy Efficient interactive Goal programming Approach for Multi-objective Transportation Problems

International Journal of Applied and Computational Mathematics 2017年第2期3卷 505-525页

作者： Singh, Pitam Kumari, Saru Singh, Priyamvada Department of Mathematics Motilal Nehru National Institute of Technology Allahabad Allahabad India Department of Mathematics C.C.S University Campus Meerut India Department of Earth and Planetary Sciences University of Allahabad Allahabad India

Multi-objective transportation problem (MOTP) is a special case of vector minimization linear optimization problem with equality constraints and the objectives are conflicting in nature. Due to the conflicting nature of objectives, no method is available to find single optimal solution for MOTP. All the methods can find only the compromise solution. This paper presents an efficient method for solving MOTP to find fuzzy efficient and compromise solution using the qualities of three well known approaches i.e. (i) fuzzy programming, (ii) goal programming, (iii) interactive programming. In this approach, fuzzy goals are decided by the decision maker (DM) for each objectives and membership functions are constructed for each objective. Then the method is developed using fuzzy set theory and the best quality of the developed method is that the decision maker is focussed only in the part of evaluation of the solution at each step using the acceptable terms and conditions. The present method is the extension of Waeil and Lee (Omega 34:158–166, 2006). To measure the efficiency of the method, some distance metric functions are used and it is verified by two numerical examples. The results are compared with previous reported work for the same numerical problems. © 2016, Springer India Pvt. Ltd.

关键词： Fuzzy goal programming Fuzzy multi-objective transportation programming interactive programming Multi-objective programming Multi-objective transportation problem

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interactive Robot programming Inspired by Dog Training: An Exploratory Study 24

Interactive Robot Programming Inspired by Dog Training: An E...

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19th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2024

作者： Schrage-Prent, Nienke Preciado Vanegas, Daniel F. Baraka, Kim Department of Computer Science Free University Amsterdam Amsterdam Netherlands Department of Communication Science Free University Amsterdam Amsterdam Netherlands

ISBN: (纸本)9798400703232

programming a robot takes time, effort, and expert knowledge. As robots find their way to our personal spaces, it becomes urgent to investigate more intuitive methods to program them. An emerging field of research has focused on developing systems that are easy for non-expert users to understand and train. This paper explores the premise that dog training methods could inspire interactive programming methods for robots. In collaboration with dog trainers, we designed an interactive programming method for a robot. We evaluated our method in a Wizard-of-Oz study with 18 participants and compared it with programming the same behavior on a graphical programming software. Results show significant differences in usability scores, with the method inspired by dog training being perceived as more usable, easier, more fun, and more personal. This suggests that robot programming methods based on dog training could benefit a broader range of end-users, allowing them to interactively program new behaviors on robots in richer and more intuitive ways. © 2024 Copyright held by the owner/author(s)

关键词： dog training human robot interaction interactive programming

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The Design and Implementation of a Table Driven, interactive Diagnostic programming System

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Communications of the ACM 1976年第11期19卷 609-616页

作者： Wilcox, Thomas R. Davis, Alan M. Tindall, Michael H. Department of Computer Science University of Illinois Urbana-Champaign Urbana IL 61801 United States

CAPS is a highly interactive diagnostic compiler/interpreter that allows beginning programmers to prepare, debug, and execute fairly simple programs at a graphics display terminal. Complete syntax checking and most semantic analysis is performed as the program is entered and as it is subsequently edited. Analysis is performed character by character. The most remarkable feature of CAPS is its ability to automatically diagnose errors both at compile time and at run time. Errors are not automatically corrected. Instead, CAPS interacts with the student to help him find the cause of his error. Most components of CAPS are table driven, both to reduce the space needed for implementation and to increase the flexibility of the multilingual system. Over 500 students have used CAPS to learn Fortran, PL/I, or Cobol in conjunction with a computer assisted course on introductory computer science. © 1976, ACM. All rights reserved.

关键词： computer assisted instruction computer science education debugging error correction interactive programming interpreters table driven compilers

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interactive random fuzzy two-level programming through possibility-based probability model

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INFORMATION SCIENCES 2013年 239卷 191-200页

作者： Sakawa, Masatoshi Matsui, Takeshi Hiroshima Univ Fac Engn Higashihiroshima 7398527 Japan

This paper considers interactive decision making methods for random fuzzy two-level linear programming problems. Assuming that the decision makers concern about the probabilities that their own objective function values are smaller than or equal to certain target values, fuzzy goals of the decision makers for the probabilities are introduced. Then, the possibility-based probability model to maximize the degrees of possibility with respect to the attained probability is considered. interactive fuzzy nonlinear programming to obtain a satisfactory solution for the decision maker at the upper level in consideration of the cooperative relation between decision makers is presented. An illustrative numerical example demonstrates the feasibility and efficiency of the proposed method. (C) 2013 Elsevier Inc. All rights reserved.

关键词： Two-level programming Random fuzzy programming Possibility Probability maximization interactive programming

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An interactive fuzzy satisficing method for multiobjective stochastic linear programming problems through an expectation model

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2003年第3期145卷 665-672页

作者： Sakawa, M Kato, K Nishizaki, I Hiroshima Univ Grad Sch Engn Fac Engn Dept Artificial Complex Syst Engn Higashihiroshima 7398527 Japan

For decision making problems involving uncertainty, both stochastic programming as an optimization method based on the theory of probability and fuzzy programming representing the ambiguity by fuzzy concept have been developing in various,ways. In this paper, we focus on multiobjective linear programming problems with random variable coefficients in objective functions and/or constraints. For such problems, as a fusion of these two approaches, after incorporating fuzzy goals of the decision maker for the objective functions, we propose an interactive fuzzy satisficing method for the expectation model to derive a satisficing solution for the decision maker. An illustrative numerical example is provided to demonstrate the feasibility of the proposed method. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： multicriteria analysis linear programming stochastic programming fuzzy programming interactive programming

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An interactive fuzzy satisficing method for general multiobjective 0-1 programming problems through genetic algorithms with double strings based on a reference solution

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FUZZY SETS AND SYSTEMS 2002年第3期125卷 289-300页

作者： Sakawa, M Kato, K Hiroshima Univ Fac Engn Dept Ind & Syst Engn Higashihiroshima 7398527 Japan

In this paper, focusing on general multiobjective 0-1 programming problems involving positive and negative coefficients, we propose an interactive fuzzy satisficing method by extending our previous genetic algorithms with double strings for multiobjective multidimensional 0-1 knapsack problems. In the extended genetic algorithms, a new decoding algorithm for individuals represented by double strings which maps each individual to a feasible solution is proposed through the introduction of backtracking and individual modification. After examining the feasibility and efficiency of the extended genetic algorithms with double strings using a lot of 0-1 programming problems involving positive and negative coefficients, an illustrative numerical example demonstrated the feasibility and efficiency of the proposed interactive fuzzy satisficing method. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： multicriteria analysis genetic algorithms 0-1 programming fuzzy programming interactive programming

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An interactive fuzzy satisficing method for multiobjective linear programming problems with random variable coefficients through a probability maximization model

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FUZZY SETS AND SYSTEMS 2004年第2期146卷 205-220页

作者： Sakawa, M Kato, K Katagiri, H Hiroshima Univ Grad Sch Engn Departificial Complex Syst Engn Higashihiroshima 7398527 Japan

Two major approaches to deal with randomness or ambiguity involved in mathematical programming problems have been developed. They are stochastic programming approaches and fuzzy programming approaches. In this paper, we focus on multiobjective linear programming problems with random variable coefficients in objective functions and/or constraints. Using the probability maximization model to maximize the probability that each objective function becomes a certain value under chance constrained conditions, the stochastic programming problems are transformed into deterministic ones. As a fusion of stochastic approaches and fuzzy ones, after determining the fuzzy, goals of the decision maker, an interactive fuzzy satisficing method to derive a satisficing solution for the decision maker by updating the reference membership levels is presented. An illustrative numerical example is provided to demonstrate the feasibility of the proposed method. (C) 2004 Elsevier B.V. All rights reserved.

关键词： fuzzy mathematical programming multi criteria analysis linear programming stochastic programming interactive programming

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Comparative studies in interactive multiple objective mathematical programming

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1996年第2期89卷 408-422页

作者： Aksoy, Y Butler, TW Minor, ED WAYNE STATE UNIV DEPT FINANCE & BUSINESS ECON DETROIT MI 48202 USA VIRGINIA COMMONWEALTH UNIV DEPT DECIS SCI & BUSINESS LAW RICHMOND VA 23284 USA

In the past two decades, there has been a significant increase in the number of interactive algorithms proposed for solving multiple objective mathematical programming (MOMP) problems. Most of these procedures have neither been tested in real decision making situations, nor compared to each other. In this study, we emphasize the importance of comparative studies of interactive MOMP procedures and present a state of the art review. Our scope is limited to the comparisons of interactive procedures for solving deterministic, linear, integer or nonlinear constrained multiple objective optimization problems involving a single decision maker.

关键词： multi-criteria analysis interactive programming comparative studies experimentation

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An interactive fuzzy satisficing method for multiobjective stochastic linear programming problems using chance constrained conditions

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Journal of Multi-Criteria Decision Analysis 2002年第3期11卷 125-137页

作者： Sakawa, Masatoshi Kato, Kosuke Department of Artificial Complex Systems Engineering Graduate School of Engineering Hiroshima University Japan

Two major approaches to deal with randomness or ambiguity involved in mathematical programming problems have been developed. They are stochastic programming approaches and fuzzy programming approaches. In this paper, we focus on multiobjective linear programming problems with random variable coefficients in objective functions and/or constraints. Using chance constrained programming techniques, the stochastic programming problems are transformed into deterministic ones. As a fusion of stochastic approaches and fuzzy ones, after determining the fuzzy goals of the decision maker, interactive fuzzy satisficing methods to derive a satisficing solution for the decision maker by updating the reference membership levels is presented. © 2003 John Wiley & Sons, Ltd.

关键词： Fuzzy mathematical programming interactive programming Linear programming Multicriteria analysis Stochastic programming

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Integrating interactive performance analysis in Jupyter Notebooks for parallel programming education

Integrating interactive performance analysis in Jupyter Note...

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1st International Conference on Smart Energy Systems and Artificial Intelligence (SESAI)

作者： Oden, Lena Noelp, Klaus Brauner, Philipp Univ Hagen Comp Engn Hagen Germany Rhein Westfal TH Aachen Human Comp Interact Ctr Aachen Germany

ISBN: (纸本)9798350364613;9798350364606

Understanding the performance behavior of parallel applications is important in many ways, but doing so is not easy. Most open source analysis tools are written for the command line. We are building on these proven tools to provide an interactive performance analysis experience within Jupyter Notebooks when developing parallel code with MPI, OpenMP, or both. Our solution makes it possible to measure the execution time, perform profiling and tracing, and visualize the results within the notebooks. For ease of use, it provides both a graphical JupyterLab extension and a C++ API. The JupyterLab extension shows a dialog where the user can select the type of analysis and its parameters. Internally, this tool uses Score -P, Scalasca, and Cube to generate profiling and tracing data. This tight integration gives students easy access to profiling tools and helps them better understand concepts such as benchmarking, scalability and performance bottlenecks. In addition to the technical development, the article presents hands-on exercises from our well-established parallel programming course. We conclude with a qualitative and quantitative evaluation with 19 students, which shows a positive effect of the tools on the students' perceived competence.

关键词： Jupyter parallel programming performance analysis interactive programming high perfonnance computing

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