Multiple Criteria Decision Making in Finance, Insurance and by Minwir Al-Shammari, Hatem Masri

By Minwir Al-Shammari, Hatem Masri

This e-book is dedicated to fresh advancements and purposes of a number of standards selection relief instruments within the box of finance, coverage and funding. It illustrates contemporary equipment and methods designed to unravel difficulties relating to finance, assurance and portfolio choice formulated via a mathematical programming framework and for which a lot of conflicting and incommensurable pursuits (criteria, attributes) is concurrently optimized. The booklet introduces researchers and practitioners to contemporary theoretical and methodological advancements in multi-attributes portfolio choice, a number of standards research in finance, coverage and funding. it really is in response to chosen and invited papers awarded and mentioned on the 2013 foreign convention on Multidimensional Finance, assurance and funding (ICMFII’13), held on the university of commercial management on the college of Bahrain from twenty fifth to twenty seventh November 2013 with the co-sponsorship of the overseas Society on a number of standards selection Making and the Institute for Operations examine and the administration Sciences - MCDM section.

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W. (1952). Chance constraints and normal deviates. Journal of the American Statistical Association, 57, 134–148. , & Cooper, W. W. (1959). Chance-constrained programming. Management Science, 6, 73–80. , Cooper, W. , & Ferguson, R. (1955). Optimal estimation of executive compensation by linear programming. Management Science, 1, 138–151. Engwerda, J. (2007). Multicriteria dynamic optimization problems and cooperative dynamic games (CentER Working Paper No. 2007-41). Tilburg University. , & Rocca, M.

P À where wþ i and wi are the weights corresponding to positive and negative deviations, respectively. The DM can express the relative importance of the objectives by 38 B. Aouni et al. providing a level of satisfaction of each positive and negative deviation. As a result, the GP model with satisfaction function is Max Z ¼ Xp i¼1 À Á À Á þ þ À À þ wÀ wþ i Fi δ i i Fi δ i ð8Þ Subject to: ðb þ f i ðt, xðtÞ, uðtÞÞdt þ δÀ i À δ i ¼ gi , i ¼ 1 . . p a x_ ðtÞ ¼ hðt, xðtÞ, uðtÞÞ x ð aÞ ¼ x a x ð bÞ ¼ x b u2U 0 δÀ i αÀ iv ð8i 2 I Þ; 0 δþ i αþ iv ð8i 2 I Þ: The above two alternative formulations (7) and (8), after discretization of both integrals and differential equations, can be solved as static optimization problems.

1952). Chance constraints and normal deviates. Journal of the American Statistical Association, 57, 134–148. , & Cooper, W. W. (1959). Chance-constrained programming. Management Science, 6, 73–80. , Cooper, W. , & Ferguson, R. (1955). Optimal estimation of executive compensation by linear programming. Management Science, 1, 138–151. Engwerda, J. (2007). Multicriteria dynamic optimization problems and cooperative dynamic games (CentER Working Paper No. 2007-41). Tilburg University. , & Rocca, M.

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