Abstract
One of the main success stories in the evolutionary computation (EC) field is the use of EC framework to solve multi-criterion optimization problems. These problems give rise to a set of trade-off Pareto-optimal solutions, instead of a single optimal solution; hence a population-based EC framework is a natural choice for solving them. Starting in the early nineties with a few parameter-dependent algorithms, the research and application of evolutionary multi-criterion optimization (EMO) algorithms has become a field of its own, by attracting mathematicians, computer scientists, engineers, economists, managers, and entrepreneurs. In this chapter, we provide a chronological account of key contributions which kept the field alive, useful, and vibrant. A bibliometric study of published materials on the topic is also provided to paint a picture of the rise and the popularity of the field.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
