Modeling and solving alternative financial solutions seeking

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January 2015, 11(1): 145-170. doi: 10.3934/jimo.2015.11.145

Modeling and solving alternative financial solutions seeking

Emmanuel Frénod ^1, , Jean-Philippe Gouigoux ^2, and Landry Touré ^2,

1.	Université de Bretagne-Sud, UMR 6205, LMBA, F-56000 Vannes, France
2.	MGDIS, Parc d'Innovation de Bretagne Sud, F-56038 Vannes, France, France

Received April 2013 Revised December 2013 Published May 2014

Abstract
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In this paper we model the working of local community finances. As a result of this first step, we obtain a systemic model that is used to formalize the problem of Alternative Financial Solutions Seeking, which consists in building a collection of Alternative Multi-Year Prospective Budgets from two Multi-Year Prospective Budgets built by a finance expert. The modeling and formalization steps are led in a way that allows us to implement a software code for Alternative Financial Solutions Seeking based on a Genetic Like Algorithm.

Keywords: systemic modeling, optimization, Finance modeling, local communities, genetic algorithms..

Mathematics Subject Classification: Primary: 90C15, 62P20, 68Uxx, 93A30; Secondary: 91G4.

Citation: Emmanuel Frénod, Jean-Philippe Gouigoux, Landry Touré. Modeling and solving alternative financial solutions seeking. Journal of Industrial & Management Optimization, 2015, 11 (1) : 145-170. doi: 10.3934/jimo.2015.11.145

References:

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[12]	K. Ilinski, Physics of Finance : Gauge Modelling in Non-Equilibrium Pricing,, Wiley, (2001). Google Scholar
[13]	C. Mattheck and S. Burkhardt, A new method of structural shape optimization based on biological growth,, International Journal of Fatigue, 12 (1990), 185. doi: 10.1016/0142-1123(90)90094-U. Google Scholar
[14]	R. Musgrave, The Theory of Public Finance : A Study in Public Economy,, McGraw-Hill, (1959). Google Scholar
[15]	H. S. Rosen, Public finance,, The Encyclopedia of Public Choice, (2004), 252. doi: 10.1007/978-0-306-47828-4_21. Google Scholar
[16]	Chen S.-H. (ed.), Genetic Algorithms and Genetic Programming in Computational Finance,, Kluwer Academic Publishers, (2002). Google Scholar
[17]	C. Soh and J. Yang, Fuzzy controlled genetic algorithm search for shape optimization,, Journal of Computing in Civil Engineering, 10 (1996), 143. doi: 10.1061/(ASCE)0887-3801(1996)10:2(143). Google Scholar
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show all references

References:

[1]	La Qualité Comptable au service d'une gestion performante des collectivités locales - Guide des bonnes pratiques Num 18, Technical report,, Académie des sciences et techniques comptables financières., (). Google Scholar
[2]	Annexe Num 1: Plan de comptes développé des communes de 500 habitants et plus au 1ier janvier 2009, Technical report, Plan M14 de Comptabilité, French State Secretary for Finance,, (, (2009). Google Scholar
[3]	D. Beasley, D. Bull and R. Martin, An overview of genetic algorithms. part 1, fundamentals,, University Computing, 15 (1993), 58. Google Scholar
[4]	D. Beasley, D. Bull and R. Martin, An overview of genetic algorithms. part 2, research topics,, University Computing, 15 (1993), 170. Google Scholar
[5]	C. Castro, C. Antònio and L. Sousa, Optimisation of shape and process parameters in metal forging using genetic algorithms,, Journal of Materials Processing Technology, 146 (2004), 356. doi: 10.1016/j.jmatprotec.2003.11.027. Google Scholar
[6]	L. Davis, Handbook of Genetic Algorithms,, Van Nostrand Reinhold, (1991). Google Scholar
[7]	K. De Jong, Proceedings of the Evolutionary Algorithms in Engineering Computer Science (EUROGEN99), chapter Evolutionary computation: Recent developments and open issues, 43-54,, University of Jyvskyl Finland, (1999). Google Scholar
[8]	E. Fama, Market efficiency, long-term returns, and behavioral finance,, Journal of Financial Economics, 49 (1998), 283. doi: 10.2139/ssrn.15108. Google Scholar
[9]	P. Fourie and A. Groenwold, The particle swarm optimization algorithm in size and shape optimization,, Structural and Multidisciplinary Optimization, 23 (2002), 259. doi: 10.1007/s00158-002-0188-0. Google Scholar
[10]	D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning,, 1st edition, (1989), 07. Google Scholar
[11]	V. Goodman and J. G. Stampfli, The Mathematics of Finance: Modeling and Hedging,, American Mathematical Society, (2001). Google Scholar
[12]	K. Ilinski, Physics of Finance : Gauge Modelling in Non-Equilibrium Pricing,, Wiley, (2001). Google Scholar
[13]	C. Mattheck and S. Burkhardt, A new method of structural shape optimization based on biological growth,, International Journal of Fatigue, 12 (1990), 185. doi: 10.1016/0142-1123(90)90094-U. Google Scholar
[14]	R. Musgrave, The Theory of Public Finance : A Study in Public Economy,, McGraw-Hill, (1959). Google Scholar
[15]	H. S. Rosen, Public finance,, The Encyclopedia of Public Choice, (2004), 252. doi: 10.1007/978-0-306-47828-4_21. Google Scholar
[16]	Chen S.-H. (ed.), Genetic Algorithms and Genetic Programming in Computational Finance,, Kluwer Academic Publishers, (2002). Google Scholar
[17]	C. Soh and J. Yang, Fuzzy controlled genetic algorithm search for shape optimization,, Journal of Computing in Civil Engineering, 10 (1996), 143. doi: 10.1061/(ASCE)0887-3801(1996)10:2(143). Google Scholar
[18]	C. Tiebout, A pure theory of local expenditures,, Journal of Political Economy, 64 (1956), 416. doi: 10.1086/257839. Google Scholar

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