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Digital Library

of the European Council for Modelling and Simulation

 

Title:

Backbone Strategy For Unconstrained Continuous Optimization

Authors:

Michael Feldmeier, Thomas Husslein

Published in:

 

 

 

(2017).ECMS 2017 Proceedings Edited by: Zita Zoltay Paprika, Péter Horák, Kata Váradi, Péter Tamás Zwierczyk, Ágnes Vidovics-Dancs, János Péter Rádics

European Council for Modeling and Simulation. doi:10.7148/2017

 

 

ISBN: 978-0-9932440-4-9/

ISBN: 978-0-9932440-5-6 (CD)

 

 

31st European Conference on Modelling and Simulation,

Budapest, Hungary, May 23rd – May 26th, 2017

 

Citation format:

Michael Feldmeier, Thomas Husslein (2017). Backbone Strategy For Unconstrained Continuous Optimization, ECMS 2017 Proceedings Edited by: Zita Zoltay Paprika, Péter Horák, Kata Váradi, Péter Tamás Zwierczyk, Ágnes Vidovics-Dancs, János Péter Rádics European Council for Modeling and Simulation. doi: 10.7148/2017-0529

 

DOI:

https://doi.org/10.7148/2017-0529

Abstract:

Backbones in optimization problems are structures within the decision variables that are common to all global optima. Identifying those backbones in a deterministic manner is at least as hard as solving the original problem to optimality because all optimal solutions to the problem have to be known. A number of different algorithms have been proposed which use heuristically determined backbones to speed up discrete combinatorial optimization algorithms by eliminating these backbones and thus reducing the dimensionality of the optimization problem to be solved in each step. In this paper we extend the concept of backbones to real-valued optimization. We propose a definition of such backbones and introduce means to identify them and determine their value by the use of a genetic algorithm. We compare the performance of the resulting algorithm with an ordinary optimization procedure on a widely used nonlinear and unconstrained optimization benchmark. We observe that our backbone strategy is superior in terms of both convergence speed and quality of the resulting solutions. Limitations of this first approach and ideas how to resolve them in future work are considered.

 

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