NDLI: Trends and challenges in dynamic optimization problems

Content Provider	IEEE Xplore Digital Library
Author	Ahsan, R. Shahzad, W. Baig, A.R.
Copyright Year	2011
Description	Author affiliation: National University of Computer and Emerging Sciences, Computer Science Department, Sector H-11/4, Islamabad, Pakistan (Ahsan, R.; Shahzad, W.; Baig, A.R.)
Abstract	This paper presents the challenges and problems faced in dynamic environment optimization problems. Real world problems are mostly dynamic thus such algorithms are required which can track the moving optima. Classical Optimization algorithm searches sequentially for the solution and are based on differential equations. In order to track the moving optima algorithm will have to be restarted and there is no guarantee that algorithm will find the optimum solution. On the other, Evolutionary algorithms are more suitable for such kind of problems as they can find the multiple optima in parallel. Evolutionary algorithms can track the optima and then repeatedly balance the need to exploit known optima with the need to search for new optima. A number of techniques have been proposed to deal with the dynamic environment problems. Different challenges and problems faced in dynamic environment whether it is for a multimodal functions or multi-objective have been discussed here.
Starting Page	283
Ending Page	288
File Size	815981
Page Count	6
File Format	PDF
ISBN	9781457721519
e-ISBN	9781457721526
DOI	10.1109/HIS.2011.6122119
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-05
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Shape Heuristic algorithms Dynamic Environment Classical Optimization (CO) Evolutionary computation Dynamic scheduling Evolutionary Algorithms (EA) Optimization Hybrid intelligent systems
Content Type	Text
Resource Type	Article

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