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Intelligent Engineering Systems through Artificial Neural Networks
Editor
Cihan H. Dagli
Cihan H. Dagli
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K. Mark Bryden
K. Mark Bryden
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Steven M. Corns
Steven M. Corns
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Mitsuo Gen
Mitsuo Gen
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Kagan Tumer
Kagan Tumer
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Gürsel Süer
Gürsel Süer
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ISBN:
9780791802953
No. of Pages:
636
Publisher:
ASME Press
Publication date:
2009

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.

Abstract
1. Introduction
2. Statement of the Problem
3. Bacterial Foraging Optimization Algorithm
4. MBFOA For Engineering Design
5. Experiments and Results
6. Conclusions and Future Work
References
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