A collection of test problems for constrained global optimization algorithms
A collection of test problems for constrained global optimization algorithms
Test Examples for Nonlinear Programming Codes
Test Examples for Nonlinear Programming Codes
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Constrained Global Optimization by Constraint Partitioning and Simulated Annealing
ICTAI '06 Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence
Evolutionary algorithms, homomorphous mappings, and constrained parameter optimization
Evolutionary Computation
Large scale evolutionary optimization using cooperative coevolution
Information Sciences: an International Journal
A simple ranking and selection for constrained evolutionary optimization
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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This paper examines a new way of dividing computational tasks into smaller interacting components, in order to effectively solve constrained optimization problems. In dividing the tasks, we propose problem decomposition, and the use of GAs as the solution approach. In this paper, we consider problems with block angular structures with or without overlapping variables. We decompose not only the problem but also appropriately the chromosome for different components of the problem. We also design a communication process for exchanging information between the components. The approach can be implemented for solving large scale optimization problems using parallel machines. A number of test problems have been solved to demonstrate the use of the proposed approach. The results are very encouraging.