English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/55941
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:

Solving nonconvex climate control problems: Pitfalls and algorithm performances

AuthorsMoles, Carmen G.; Banga, Julio R. ; Keller, Klaus
KeywordsGlobal optimization
Optimal control
Climate thresholds
Issue Date2004
CitationApplied Soft Computing 5(1): 35-44 (2004)
AbstractGlobal optimization can be used as the main component for reliable decision support systems. In this contribution, we explore numerical solution techniques for nonconvex and nondifferentiable economic optimal growth models. As an illustrative example, we consider the optimal control problem of choosing the optimal greenhouse gas emissions abatement to avoid or delay abrupt and irreversible climate damages. We analyze a number of selected global optimization methods, including adaptive stochastic methods, evolutionary computation methods and deterministic/hybrid techniques. Differential evolution (DE) and one type of evolution strategy (SRES) arrived to the best results in terms of objective function, with SRES showing the best convergence speed. Other simple adaptive stochastic techniques were faster than those methods in obtaining a local optimum close to the global solution, but mis-converged ultimately.
Description10 páginas, 4 figuras, 1 tabla
Publisher version (URL)http://dx.doi.org/10.1016/j.asoc.2004.03.011
Appears in Collections:(IIM) Artículos
Files in This Item:
There are no files associated with this item.
Show full item record
Review this work

Related articles:

WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.