I.G.P. Asto Buditjahjanto, Hajime Miyauchi
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. © 2011 World Scientific Publishing Company.
Department of Electrical Engineering, Universitas Negeri Surabaya, Kampus Ketintang, Surabaya, Indonesia; Department of Computer Science and Electrical Engineering, Kumamoto University, Kumamoto, Japan
