Multiobjective cuckoo search for design optimization
Full text is not in this repository.
Official URL: http://dx.doi.org/10.1016/j.cor.2011.09.026
This item is available in the Library Catalogue
Many design problems in engineering are typically multiobjective, under complex nonlinear constraints. The algorithms needed to solve multiobjective problems can be significantly different from the methods for single objective optimization. Computing effort and the number of function evaluations may often increase significantly for multiobjective problems. Metaheuristic algorithms start to show their advantages in dealing with multiobjective optimization. In this paper, we formulate a new cuckoo search for multiobjective optimization. We validate it against a set of multiobjective test functions, and then apply it to solve structural design problems such as beam design and disc brake design. In addition, we also analyze the main characteristics of the algorithm and their implications.
|Keywords (uncontrolled):||Cuckoo search; Metaheuristic; Multiobjective; Optimization|
|Research Areas:||Middlesex University Schools and Centres > School of Science and Technology > Design Engineering and Mathematics|
|Deposited On:||15 Nov 2012 11:18|
|Last Modified:||04 Dec 2014 17:06|
Repository staff only: item control page
Full text downloads (NB count will be zero if no full text documents are attached to the record)
Downloads per month over the past year