An Analysis of black-box optimization problems in reinsurance : evolutionary-based approaches
Salcedo-Sanz, Sancho
Carro Calvo, L.
Claramunt Bielsa, M. Mercè, 1964-
Castañer, Anna
Mármol, Maite
Xarxa de Referència en Economia Aplicada (XREAP)

Imprint: Xarxa de Referència en Economia Aplicada (XREAP) 2013
Description: 34 p.
Abstract: Black-box optimization problems (BBOP) are de ned as those optimization problems in which the objective function does not have an algebraic expression, but it is the output of a system (usually a computer program). This paper is focussed on BBOPs that arise in the eld of insurance, and more speci cally in reinsurance problems. In this area, the complexity of the models and assumptions considered to de ne the reinsurance rules and conditions produces hard black-box optimization problems, that must be solved in order to obtain the optimal output of the reinsurance. The application of traditional optimization approaches is not possible in BBOP, so new computational paradigms must be applied to solve these problems. In this paper we show the performance of two evolutionary-based techniques (Evolutionary Programming and Particle Swarm Optimization). We provide an analysis in three BBOP in reinsurance, where the evolutionary-based approaches exhibit an excellent behaviour, nding the optimal solution within a fraction of the computational cost used by inspection or enumeration methods.
Rights: L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons: Creative Commons
Language: Anglès.
Series: Xarxa de Referència en Economia Aplicada (XREAP): Documents de treball de la Xarxa de Referència en Economia Aplicada (XREAP)
Series: XREAP ; 2013-04
Document: workingPaper
Subject: Matemàtica actuarial ; Reassegurances ; Risc (Assegurances)

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34 p, 230.1 KB

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 Record created 2017-10-16, last modified 2019-02-02

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