Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Design of truss-structures for minimum weight using genetic algorithms
Finite Elements in Analysis and Design
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Multiple Objective Optimization with Vector Evaluated Genetic Algorithms
Proceedings of the 1st International Conference on Genetic Algorithms
Comparison Of Methods For Using Reduced Models To Speed Up Design Optimization
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Gado: a genetic algorithm for continuous design optimization
Gado: a genetic algorithm for continuous design optimization
Learning to be selective in genetic-algorithm-based design optimization
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Muiltiobjective optimization using nondominated sorting in genetic algorithms
Evolutionary Computation
Using a genetic algorithm to optimize the gape of a snake jaw
Proceedings of the 2004 ACM symposium on Applied computing
Memetic Algorithm Based on a Constraint Satisfaction Technique for VRPTW
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Artificial immune system for multi-objective design optimization of composite structures
Engineering Applications of Artificial Intelligence
On the Effect of the Steady-State Selection Scheme in Multi-Objective Genetic Algorithms
EMO '09 Proceedings of the 5th International Conference on Evolutionary Multi-Criterion Optimization
Multi-objective evolutionary simulation-optimisation of a real-world manufacturing problem
Robotics and Computer-Integrated Manufacturing
Constraint handling in multiobjective evolutionary optimization
IEEE Transactions on Evolutionary Computation
Multi-objective optimization for channel allocation in mobile computing using NSGA-II
International Journal of Network Management
Polygonal approximation of digital curves using a multi-objective genetic algorithm
GREC'05 Proceedings of the 6th international conference on Graphics Recognition: ten Years Review and Future Perspectives
Asynchronous master/slave moeas and heterogeneous evaluation costs
Proceedings of the 14th annual conference on Genetic and evolutionary computation
International Journal of Applied Metaheuristic Computing
A Multiobjective Particle Swarm Optimizer for Constrained Optimization
International Journal of Swarm Intelligence Research
International Journal of Swarm Intelligence Research
Evolutionary design of optical waveguide with multiple objectives
ACSC '12 Proceedings of the Thirty-fifth Australasian Computer Science Conference - Volume 122
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In this paper we propose two novel approaches for solving constrained multi-objective optimization problems using steady state GAs. These methods are intended for solving real-world application problems that have many constraints and very small feasible regions. One method called Objective Exchange Genetic Algorithm for Design Optimization (OEGADO) runs several GAs concurrently with each GA optimizing one objective and exchanging information about its objective with the others. The other method called Objective Switching Genetic Algorithm for Design Optimization (OSGADO) runs each objective sequentially with a common population for all objectives. Empirical results in benchmark and engineering design domains are presented. A comparison between our methods and Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) shows that our methods performed better than NSGA-II for difficult problems and found Pareto-optimal solutions in fewer objective evaluations. The results suggest that our methods are better applicable for solving real-world application problems wherein the objective computation time is large.