Design patterns: elements of reusable object-oriented software
Design patterns: elements of reusable object-oriented software
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Parallel predator---prey interaction for evolutionary multi-objective optimization
Natural Computing: an international journal
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Engineering design increasingly uses computer simulation models coupled with optimization algorithms to find the best design that meets the customer constraints within a time constrained deadline. The continued application of Moore's law combined with linear speedups of coarse grained parallelization will allow more designs to be evaluated in shorter periods of time. This paper presents a scalable, standards based framework that uses web services and grid services with a multiple objective genetic algorithm to solve continuous, mixed integer, single objective or multiple objective nonlinear, constrained design problems. Test data is provided to validate a linear speedup based on the number of processors and to show the robustness of the genetic algorithm on a set of 10 design problems.