A behavioral-based meta-heuristic for robust global trajectory optimization

Vasile, M. (2008) A behavioral-based meta-heuristic for robust global trajectory optimization. In: 2007 IEEE Congress on Evolutionary Computation, CEC 2007. IEEE Computer Society: Piscataway, NJ, pp. 2056-2063. ISBN 9781424413409

Abstract

This paper presents a behavioral-based metaheuristic for black-box problems of global trajectory optimization. This approach is shown to perform an efficient exploration of the solution space without sacrificing local convergence. The proposed meta-heuristic models the search for a solution as an action-selection process: a number of agents, forming a population, are endowed with a number of individualistic and social behaviors. The combination of these behaviors drives the entire population toward a number of local optima and eventually to the global one. In order to improve the collection of local optima in different regions of the search space the behavioral-search has been hybridized with a domain decomposition technique. This approach was applied to two typical problems in trajectory design, demonstrating a remarkable robustness compared to the most common methods, both stochastic and deterministic, for global optimization.

• Item Type: Book Sections
• Additional Information: 2007 IEEE Congress on Evolutionary Computation, CEC 2007, September 25, 2007 - September 28, 2007, Singapore
• Status: Published
• Glasgow Author(s) Enlighten ID: Vasile, Dr Massimiliano
• Authors: Vasile, M.
• College/School: College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
• Publisher: IEEE Computer Society
• ISBN: 9781424413409