Genetic algorithms (GAs) are a highly effective and efficient means of solving optimization problems. Gene encoding, fitness landscape and genetic operations are vital to successfully developing a GA. Cheong and Lai1 described a novel method, which employed an enhanced genetic algorithm with multiple populations, to optimize a fuzzy controller, and the experimental results revealed that their method was effective in producing a well-formed fuzzy rule-base. However, their encoding method and fitness function appear unnatural and inefficient. This study proposes an alternative method of concise genetic encoding and fitness design.
|Number of pages||4|
|Journal||IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics|
|State||Published - 1 Aug 2001|
- Fuzzy modeling
- Genetic algorithms