An interactive evolutionary multi-objective optimization and decision making procedure
Applied Soft Computing
An integrated framework of hybrid evolutionary computations
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Large population size IGA with individuals' fitness not assigned by user
Applied Soft Computing
Interactive evolution for the procedural generation of tracks in a high-end racing game
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Interactive genetic algorithms with individual's fuzzy fitness
Computers in Human Behavior
Evolutionary algorithms for optimization problems with uncertainties and hybrid indices
Information Sciences: an International Journal
An interactive genetic algorithm based on improved sharing mechanism for automobile modeling design
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part I
Divergent exploration in design with a dynamic multiobjective optimization formulation
Structural and Multidisciplinary Optimization
An IGA-based design support system for realistic and practical fashion designs
Computer-Aided Design
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This paper emphasizes the necessity of formally bringing qualitative and quantitative criteria of ergonomic design together, and provides a novel complementary design framework with this aim. Within this framework, different design criteria are viewed as optimization objectives, and design solutions are iteratively improved through the cooperative efforts of computer and user. The framework is rooted in multiobjective optimization, genetic algorithms, and interactive user evaluation. Three different algorithms based on the framework are developed, and tested with an ergonomic chair design problem. The parallel and multiobjective approaches show promising results in fitness convergence, design diversity, and user satisfaction metrics.