Decision Support Based on Integration of Fuzzy Clusering and Multiobjective Optimization Problem for Non Player Character in Business Game

2009 ◽  
Author(s):  
Mochamad Hariadi ◽  
I. G. P. Asto Buditjahjanto ◽  
Mauridhi Hery Purnomo
Keyword(s):  
Decision Support ◽  
Multiobjective Optimization ◽  
Optimization Problem ◽  
Multiobjective Optimization Problem ◽  
Business Game

AN INTELLIGENT DECISION SUPPORT BASED ON A SUBTRACTIVE CLUSTERING AND FUZZY INFERENCE SYSTEM FOR MULTIOBJECTIVE OPTIMIZATION PROBLEM IN SERIOUS GAME

2011 ◽  
Vol 10 (05) ◽  
pp. 793-810 ◽  
Author(s):  
I. G. P. ASTO BUDITJAHJANTO ◽  
HAJIME MIYAUCHI
Keyword(s):  
Decision Support ◽  
Multiobjective Optimization ◽  
Optimization Problem ◽  
Fuzzy Inference ◽  
Subtractive Clustering ◽  
Multiobjective Optimization Problem ◽  
Optimal Solutions ◽  
Inference System ◽  
Intelligent Decision ◽  
Intelligent Decision Support

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.

scholarly journals Bus Timetabling as a Fuzzy Multiobjective Optimization Problem Using Preference-based Genetic Algorithm

1970 ◽  
Vol 24 (3) ◽  
pp. 183-191 ◽  
Author(s):  
Surafel Luleseged Tilahun ◽  
Hong Choon Ong
Keyword(s):  
Genetic Algorithm ◽  
Multiobjective Optimization ◽  
Waiting Time ◽  
Third World ◽  
Optimization Problem ◽  
Vital Role ◽  
Single Frequency ◽  
Multiobjective Optimization Problem ◽  
Fuzzy Preference

Transportation plays a vital role in the development of a country and the car is the most commonly used means. However, in third world countries long waiting time for public buses is a common problem, especially when people need to switch buses. The problem becomes critical when one considers buses joining different villages and cities. Theoretically this problem can be solved by assigning more buses on the route, which is not possible due to economical problem. Another option is to schedule the buses so that customers who want to switch buses at junction cities need not have to wait long. This paper discusses how to model single frequency routes bus timetabling as a fuzzy multiobjective optimization problem and how to solve it using preference-based genetic algorithm by assigning appropriate fuzzy preference to the need of the customers. The idea will be elaborated with an example.

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