NDLI: Evolutionary multiobjective optimization in dynamic environments: A set of novel benchmark functions

Content Provider	IEEE Xplore Digital Library
Author	Biswas, S. Das, S. Suganthan, P.N. Coello Coello, C.A.
Copyright Year	2014
Description	Author affiliation: Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore (Suganthan, P.N.) \|\| Dept. of Comput. Sci., CINVESTAV-IPN, Mexico City, Mexico (Coello Coello, C.A.) \|\| Electron. & Commun. Sci. Unit, Indian Stat. Inst., Kolkata, India (Das, S.) \|\| Dept. of Electron. & Tele-Commun. Eng., Jadavpur Univ., Kolkata, India (Biswas, S.)
Abstract	Time varying nature of the constraints, objectives and parameters that characterize several practical optimization problems have led to the field of dynamic optimization with Evolutionary Algorithms. In recent past, very few researchers have concentrated their efforts on the study of Dynamic multi-objective Optimization Problems (DMOPs) where the dynamicity is attributed to multiple objectives of conflicting nature. Considering the lack of a somewhat diverse and challenging set of benchmark functions, in this article, we discuss some ways of designing DMOPs and propose some general techniques for introducing dynamicity in the Pareto Set and in the Pareto Front through shifting, shape variation, slope variation, phase variation, and several other types. We introduce 9 benchmark functions derived from the benchmark suite used for the 2009 IEEE Congress on Evolutionary Computation competition on bound-constrained and static MO optimization algorithms. Additionally a variant of multiobjective EA based on decomposition (MOEA/D) have been put forward and tested along with peer algorithms to evaluate the newly proposed benchmarks.
Starting Page	3192
Ending Page	3199
File Size	1089327
Page Count	8
File Format	PDF
e-ISBN	9781479914883
DOI	10.1109/CEC.2014.6900487
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Benchmark testing Shape Polynomials Pareto optimization Evolutionary computation Linear programming
Content Type	Text
Resource Type	Article

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