An introduction to genetic algorithms
An introduction to genetic algorithms
ACM Computing Surveys (CSUR)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Evolutionary and Adaptive Computing in Engineering Design: The Integration of Adaptive Search Exploration and Optimization with Engineering Design Pro
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Multiobjective Satisfaction within an Interactive Evolutionary Design Environment
Evolutionary Computation
The effect of user interaction mechanisms in multi-objective IGA
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
A new design optimization framework based on immune algorithm and Taguchi's method
Computers in Industry
User-centric image segmentation using an interactive parameter adaptation tool
Pattern Recognition
Large population size IGA with individuals' fitness not assigned by user
Applied Soft Computing
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
Divergent exploration in design with a dynamic multiobjective optimization formulation
Structural and Multidisciplinary Optimization
Integrated and interactive method for solving layout optimization problems
Expert Systems with Applications: An International Journal
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Consideration of qualitative factors is an integral and necessary part of design optimization. In this paper, we consider qualitative factors as design objectives to be optimized and attempt to optimize qualitative and quantitative criteria together. Interactive evolutionary computation (IEC) provides an ideal platform to include qualitative perspectives of the designer for the optimization of a design. This paper reviews the inclusion of qualitativeness in design, makes the case for its necessity, and classifies qualitative concepts in design optimization, before moving onto a comparison between sequential single objective and multi-objective optimization with regards to simultaneous handling of qualitative and quantitative criteria. The manufacturing plant layout design problem is used as an illustrative example. We further examine the enrichment of the optimization methods by allowing human interaction with the program within the framework of IEC. The multi-objective platform is found to be superior. Finally various challenges, such as the influence of human fatigue, are discussed.