Hybrid multi-objective cuckoo search with dynamical local search

Hybrid multi-objective cuckoo search with dynamical local search Cuckoo search (CS) is a recently developed meta-heuristic, which has shown good search abilities on many optimization problems. In this paper, we present a hybrid multi-objective CS (HMOCS) for solving multi-objective optimization problems (MOPs). The HMOCS employs the non-dominated sorting procedure and a dynamical local search. The former is helpful to generate Pareto fronts, and the latter focuses on enhance the local search. In order to verify the performance of our approach HMOCS, six well-known benchmark MOPs were used in the experiments. Simulation results show that HMOCS outperforms three other multi-objective algorithms in terms of convergence, spread and distributions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Memetic Computing Springer Journals

Hybrid multi-objective cuckoo search with dynamical local search

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2017 by Springer-Verlag GmbH Germany
Subject
Engineering; Mathematical and Computational Engineering; Artificial Intelligence (incl. Robotics); Complex Systems; Control, Robotics, Mechatronics; Bioinformatics; Applications of Mathematics
ISSN
1865-9284
eISSN
1865-9292
D.O.I.
10.1007/s12293-017-0237-2
Publisher site
See Article on Publisher Site

Abstract

Cuckoo search (CS) is a recently developed meta-heuristic, which has shown good search abilities on many optimization problems. In this paper, we present a hybrid multi-objective CS (HMOCS) for solving multi-objective optimization problems (MOPs). The HMOCS employs the non-dominated sorting procedure and a dynamical local search. The former is helpful to generate Pareto fronts, and the latter focuses on enhance the local search. In order to verify the performance of our approach HMOCS, six well-known benchmark MOPs were used in the experiments. Simulation results show that HMOCS outperforms three other multi-objective algorithms in terms of convergence, spread and distributions.

Journal

Memetic ComputingSpringer Journals

Published: Jul 4, 2017

References

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