Abstract This work presents a demonstrational application of genetic algorithms (GAs) to solve sample optimization problems in the generation IV nuclear reactor core design. The new software was developed implementing novel GAs, and it applied show their capabilities by presenting an example solution two selected check whether GAs can be used successfully engineering as tool. 3600 MWth oxide co...

The design of vector quantizers (VQs) that yield minimal distortion is one of the most challenging problems in source coding. The problem of VQ design is to find a codebook that gives the least overall distortion (or equivalently, the largest signal-to-noise ratio (SNR)) for a given set of input vectors. This problem is known to be difficult as there are no known closed-form solutions. The Gene...

An optimization system based on genetic algorithms (GAs) simulating an evolutionary feedback for the design of theatres was developed. The first GA model was an optimization of the walls and the ceiling of a hall of the wide-shoebox type. The second model was an optimization of reflectors for a fan shaped outdoor theatre. The final results show that the optimized forms from both models are comp...

The design of rolling element bearings has been a challenging task in the field of Mechanical Engineering. Traditional approaches to the design optimization of such bearings have proved to be computationally time intensive and have yielded solutions that are yet to be theoretically proven optimal. While most of the real aspects of the design are never disclosed by bearing manufacturers, the com...

In this paper, the design of a PID type stabilizer is investigated using Genetic algorithms. The proposed stabilizer is applied to a single machine infinite bus system subjected to a load disturbance. Comparison with Conventional lead-lag Power System Stabilizer (CPSS) and other design methods of PID stabilizers shows the out performance of the proposed design. Furthermore, the proposed stabili...