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An Intelligent Decision Support Based On A Subtractive Clustering And Fuzzy Inference System For Multiobjective Optimization Problem In Serious Game

Author

Listed:
  • I. G. P. ASTO BUDITJAHJANTO

    (Department of Electrical Engineering, Universitas Negeri Surabaya, Kampus Ketintang, Surabaya, Indonesia)

  • HAJIME MIYAUCHI

    (Department of Computer Science and Electrical Engineering, Kumamoto University, Kumamoto, Japan)

Abstract

Learning decision making through playing a game is an interesting activity for the decision maker or player. In this paper, a multiobjective optimization problem for economic and emission dispatch in which the player can learn about the tradeoff between fuel cost (economic) and emission problems to achieve optimal decisions is considered. A nonplayer character (NPC) is an entity that is built to provide intelligent decision support for the player. The proposed approach is carried out in two stages for the NPC module: the first stage uses the nondominated sorting genetic algorithm II method to solve the multiobjective optimization problem; this stage produces some optimal solutions. The next stage uses subtractive clustering to cluster optimal solutions; furthermore, these clusters are used to build a fuzzy inference system based on the Mamdani type. In this stage, players can select the best decision offered by the NPC.

Suggested Citation

  • I. G. P. Asto Buditjahjanto & Hajime Miyauchi, 2011. "An Intelligent Decision Support Based On A Subtractive Clustering And Fuzzy Inference System For Multiobjective Optimization Problem In Serious Game," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 10(05), pages 793-810.
    • Handle: RePEc:wsi:ijitdm:v:10:y:2011:i:05:n:s0219622011004579
    DOI: 10.1142/S0219622011004579
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