Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/109684
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Type: Book chapter
Title: Evolutionary computation for real-world problems
Author: Bonyadi, M.
Michalewicz, Z.
Citation: Challenges in Computational Statistics and Data Mining, 2016 / Matwin, S., Mielniczuk, J. (ed./s), pp.1-24
Publisher: Springer
Publisher Place: Switzerland
Issue Date: 2016
Series/Report no.: Studies in Computational Intelligence; 605
ISBN: 3319187805
9783319187808
Statement of
Responsibility: 
Mohammad Reza Bonyadi and Zbigniew Michalewicz
Abstract: In this paper we discuss three topics that are present in the area of real-world optimization, but are often neglected in academic research in evolutionary computation community. First, problems that are a combination of several interacting sub-problems (so-called multi-component problems) are common in many real-world applications and they deserve better attention of research community. Second, research on optimisation algorithms that focus the search on the edges of feasible regions of the search space is important as high quality solutions usually are the boundary points between feasible and infeasible parts of the search space in many real-world problems. Third, finding bottlenecks and best possible investment in real-world processes are important topics that are also of interest in real-world optimization. In this chapter we discuss application opportunities for evolutionary computation methods in these three areas.
Rights: © Springer International Publishing Switzerland 2016
RMID: 0030031988
DOI: 10.1007/978-3-319-18781-5_1
Published version: http://www.springer.com/gp/book/9783319187808
Appears in Collections:Computer Science publications

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