Subcontractor performance directly affects project success. The use of inappropriate subcontractors may result in individual work delays, cost overruns, and quality defects throughout the project. This study develops web-based Evolutionary Fuzzy Neural Networks (EFNNs) to predict subcontractor performance. EFNNs are a fusion of Genetic Algorithms (GAs), Fuzzy Logic (FL), and Neural Networks (NN...

Despite the occurrence of elegant algorithms for solving complex problem, exhaustive search has retained its significance since many real-life problems exhibit no regular structure and exhaustive search is the only possible solution. The advent of high-performance computing either via multicore processors or distributed processors emphasizes the possibility for exhaustive search by multiple sea...

Most commonly used inductive rule learning algorithms employ a hill-climbing search, whereas local pattern discovery algorithms employ exhaustive search. In this paper, we evaluate the spectrum of different search strategies to see whether separate-and-conquer rule learning algorithms are able to gain performance in terms of predictive accuracy or theory size by using more powerful search strat...

Among methods of breaking a cipher, exhaustive key search stands out as the most successful (albeit the least efficient) method. We demonstrate that various algorithmic implementations of exhaustive key search are not equally effective, and cryptosystems can be devised which make some implementations of exhaustive key search unsuccessful (in the sense that the problem these algorithms try to so...