Intelligent Engineering Systems through Artificial Neural Networks
45 Modified Bacterial Foraging Optimization for Engineering Design
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We present an adaptation of the bacterial foraging optimization algorithm (inspired on bacteria moving in their environment looking for high-nutrient areas) to solve engineering design problems. This proposal simplifies the original algorithm, proposed for unconstrained optimization, as to adapt it to solve constrained problems in numerical search spaces. The modifications look to decrease the number of parameters used in the algorithm, adding a constraint-handling mechanism and improving the communication capabilities among bacteria. The approach is tested on some well-known engineering design problems and its performance is compared against state-of-the-art algorithms. Based on the obtained results, some conclusions are established and the future work is defined.