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2004

Solving nonconvex climate control problems: pitfalls and algorithm performances

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Solving nonconvex climate control problems: pitfalls and algorithm performances
Global 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.
Carmen G. Moles, Julio R. Banga, Klaus Keller
Added 16 Dec 2010
Updated 16 Dec 2010
Type Journal
Year 2004
Where ASC
Authors Carmen G. Moles, Julio R. Banga, Klaus Keller
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