The paper deals with the distributed solution of simulation based nonlinear constrained optimization problems in engineering on a network of workstations. This type of non-linear optimization and control problems in engineering can be generally characterized as non{convex and non-smooth. Additionally, the involved simulation introduces certain numerical "noise\ to the solution process. These ch...

OF THE DISSERTATION The Use of Arti cial Intelligence to Improve the Numerical Optimization of Complex Engineering Designs by Mark A. Schwabacher Dissertation Directors: Thomas Ellman and Andrew Gelsey Gradient-based numerical optimization of complex engineering designs promises to produce better designs rapidly. However, such methods generally assume that the objective function and constraint ...

In this paper, a global optimization technique based on the Adaptive Response Surface Method (ARSM) is integrated with a Control Volume Finite Element Method (CVFEM) for thermofluid optimization. The objective of the optimization is to improve the thermal effectiveness of an aircraft de-icing strategy by re-designing the cooling bay surface shape. The design optimization combines the modeling o...

The genetic algorithm (GA) is an evolutionary optimization algorithm operating based upon reproduction, crossover and mutation. On the other hand, particle swarm optimization (PSO) is a swarm intelligence algorithm functioning by means of inertia weight, learning factors and the mutation probability based upon fuzzy rules. In this paper, particle swarm optimization in association with genetic a...

The genetic algorithm (GA) is an evolutionary optimization algorithm operating based upon reproduction, crossover and mutation. On the other hand, particle swarm optimization (PSO) is a swarm intelligence algorithm functioning by means of inertia weight, learning factors and the mutation probability based upon fuzzy rules. In this paper, particle swarm optimization in association with genetic a...