Solving complex, real-world problems with genetic programming (GP) can require extensive computing resources. However, the highly parallel nature of GP facilitates using a large n...
In this paper we present a method for creating scheduling heuristics for parallel proportional machine scheduling environment and arbitrary performance criteria. Genetic programmin...
A comparative study of parallel metaheuristics executed in grid environments is proposed, having as case study a genetic algorithm, a simulated annealing algorithm and a random se...
Abstract. We have investigated the adaptation of AI-based search techniques as topologyindependent fault-tolerant routing strategies on multiprocessor networks [9]. The results sho...
Evolutionary Algorithms, including Genetic Programming (GP), are frequently employed to solve difficult real-life problems, which can require up to days or months of computation. ...