NDLI: A hybrid cooperative search algorithm for constrained optimization

Content Provider	Springer Nature Link
Author	Nema, Salam Goulermas, John Y. Sparrow, Graham Helman, Paul
Copyright Year	2010
Abstract	Many engineering design problems can be formulated as constrained optimization problems which often consist of many mixed equality and inequality constraints. In this article, a hybrid coevolutionary method is developed to solve constrained optimization problems formulated as min–max problems. The new method is fast and capable of global search because of combining particle swarm optimization and gradient search to balance exploration and exploitation. It starts by transforming the problem into unconstrained one using an augmented Lagrangian function, then using two groups to optimize different components of the solution vector in a cooperative procedure. In each group, the final stage of the search procedure is accelerated by via a simple local search method on the best point reached by the preceding exploration based search. We validated the effectiveness and robustness of the proposed algorithm using several engineering problems taken from the specialised literature.
Starting Page	107
Ending Page	119
Page Count	13
File Format	PDF
ISSN	1615147X
Journal	Structural and Multidisciplinary Optimization
Volume Number	43
Issue Number	1
e-ISSN	16151488
Language	English
Publisher	Springer-Verlag
Publisher Date	2010-08-03
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Coevolutionary optimization Cooperative evolution Particle swarm optimization Engineering Design Computational Mathematics and Numerical Analysis Theoretical and Applied Mechanics
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Computer Graphics and Computer-Aided Design Control and Systems Engineering Computer Science Applications Software

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