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Erschienen in:
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2017 | OriginalPaper | Buchkapitel

15. Tug of War Optimization

verfasst von : A. Kaveh

Erschienen in: Advances in Metaheuristic Algorithms for Optimal Design of Structures

Verlag: Springer International Publishing

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Abstract

In this chapter, tug of war optimization (TWO) is presented as a newly developed nature-inspired, population-based metaheuristic algorithm. Utilizing a sport metaphor, the algorithm considers each candidate solution as a team participating in a series of rope-pulling competitions. The teams exert pulling forces on each other based on the quality of the solutions they represent. The competing teams move to their new positions according to Newtonian laws of mechanics. Unlike many other metaheuristic methods, the algorithm is formulated in such a way that considers the qualities of both of the interacting teams. TWO is applicable to global optimization of discontinuous, multimodal, non-smooth, and non-convex functions.

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Vorheriges Kapitel Global Sensitivity Analysis-Based Optimization Algorithm
Nächstes Kapitel Water Evaporation Optimization Algorithm
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Metadaten
Titel
Tug of War Optimization
verfasst von
A. Kaveh
Copyright-Jahr
2017
Buch
Advances in Metaheuristic Algorithms for Optimal Design of Structures

Print ISBN: 978-3-319-46172-4

Electronic ISBN: 978-3-319-46173-1

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-46173-1_15

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