Illustrating evolutionary computation with Mathematica
Illustrating evolutionary computation with Mathematica
Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Global Optima of Lennard-Jones Clusters
Journal of Global Optimization
Efficient Global Optimization of Expensive Black-Box Functions
Journal of Global Optimization
A first multilevel cooperative algorithm for capacitated multicommodity network design
Computers and Operations Research - Anniversary focused issue of computers & operations research on tabu search
A computational efficient covariance matrix update and a (1+1)-CMA for evolution strategies
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Developing Multi-Agent Systems with JADE (Wiley Series in Agent Technology)
Developing Multi-Agent Systems with JADE (Wiley Series in Agent Technology)
Evolutionary algorithms for constrained parameter optimization problems
Evolutionary Computation
Parallel Approaches for Multiobjective Optimization
Multiobjective Optimization
Explicit and Emergent Cooperation Schemes for Search Algorithms
Learning and Intelligent Optimization
AMA: a new approach for solving constrained real-valued optimization problems
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Emerging Trends in Soft Computing - Memetic Algorithms; Guest Editors: Yew-Soon Ong, Meng-Hiot Lim, Ferrante Neri, Hisao Ishibuchi
A flexible tolerance genetic algorithm for optimal problems with nonlinear equality constraints
Advanced Engineering Informatics
A hybrid real-parameter genetic algorithm for function optimization
Advanced Engineering Informatics
A hybrid intelligent genetic algorithm
Advanced Engineering Informatics
Music-Inspired Harmony Search Algorithm: Theory and Applications
Music-Inspired Harmony Search Algorithm: Theory and Applications
Multiagent optimization system for solving the traveling salesman problem (TSP)
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An Introduction to MultiAgent Systems
An Introduction to MultiAgent Systems
Robust Optimization for Unconstrained Simulation-Based Problems
Operations Research
Robust optimization with simulated annealing
Journal of Global Optimization
Handbook of Metaheuristics
jMetal: A Java framework for multi-objective optimization
Advances in Engineering Software
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
MAGMA: a multiagent architecture for metaheuristics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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Structural design and optimization in engineering are increasingly addressing non-standard optimization problems (NSPs). These problems are characterized by a complex topology of the optimization space with respect to nonlinearity, multimodality, discontinuity, etc. By that, NSP can only be solved by means of computer simulations. In addition, the corresponding numerical approaches applied often tend to be noisy. Typical examples for NSP occur in robust optimization, where the solution has to be robust with respect to implementation errors, production tolerances or uncertain environmental conditions. However, a generally applicable strategy for solving such problem categories always equally efficiently is not yet available. To improve the situation, a distributed agent-based optimization approach for solving NSPs is introduced in this paper. The elaborated approach consists of a network of cooperating but also competing strategy agents that wrap various strategies, especially optimization methods (e.g. SQP, DE, ES, PSO, etc.) using different search characteristics. In particular, the strategy agents contain an expert system modeling their specific behavior in an optimization environment by means of rules and facts on a highly abstract level. Further, different common interaction patterns have been defined to describe the structure of a strategy network and its interactions. For managing the complexity of NSPs using multi-agent systems (MASs) efficiently, a simulation and experimentation platform has been developed. Serving as a computational steering tool, it applies MAS technology and accesses a network of various optimization strategies. As a consequence, an elegant interactive steering, a customized modeling and a powerful visualization of structural optimization processes are established. To demonstrate the far reaching applicability of the proposed approach, numerical examples are discussed, including nonlinear function and robust optimization problems. The results of the numerical experiments illustrate the potential of the agent-based strategy network approach for collaborative solving, where observed synergy effects lead to an effective and efficient solution finding.