A decision support tool coupling a causal model and a multi-objective genetic algorithm

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3533 LNAI, Issue , 2005, Pages 628-637

  Blecic, Ivan ^a   Cecchini, Arnaldo ^a   Trunfio, Giuseppe A ^b  

^a UNIVERSITY OF SASSARI   (Italy)

^b UNIVERSITY OF CALABRIA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER AIDED SOFTWARE ENGINEERING; DECISION MAKING; GENETIC ALGORITHMS; PROBABILISTIC LOGICS;

DECISION SPACE; SOFTWARE TOOL;

ARTIFICIAL INTELLIGENCE;

EID: 26944455161     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11504894_88     Document Type: Conference Paper

References (14)

1. Stover, J., Gordon, T.J. Cross-impact analysis. Handbook of Futures Research, ed. J. Fowles. Greenwood Press, 1978
2. Gordon, T.J., Hayward, H. Initial experiments with the cross-impact method of forecasting. Futures 1(2), 1968, 100-116
3. Helmer, O. Cross-impact gaming. Futures 4, 1972, 149-167
4. Turoff, M. An alternative approach to cross-impact analysis. Technological Forecasting and Social Change 3(3), 1972, 309-339
5. Helmer, O. Problems in Future Research: Delphi and Causal Cross Impact Analysis. Futures 9, 1977, 17-31
6. Alarcòn, L.F., Ashley, D.B. Project management decision making using cross-impact analysis. Int. Journal of Project Management 16(3), 1998, 145-152
7. Pearl, J. Evidential Reasoning Using Stochastic Simulation of Causal Models. Artificial Intelligence, 32, 1987, 245-257
8. Linstone, H.A., Turoff, M. (editors). The Delphi Method: Techniques and Applications, 2002, Available at: http://www.is.njit.edu/pubs/delphibook/index. html
9. Fonseca, C.M., Fleming, P.J. An overview of evolutionary algorithms in multiobjective optimization. Evolutionary Computation 3 (1), 1995, 1-16
10. Goldberg, D. Genetic Algorithms and Evolution Strategy in Engineering and Computer Science: Recent Advances and Industrial Applications, 1998, Wiley & Sons
11. Sawaragi Y, Nakayama H, Tanino T. Theory of multiobjective optimization. 1985, Orlando, Florida: Academic Press.
12. Srinivas N, Deb K. Multiobjective function optimization using nondominated sorting genetic algorithms. Evolutionary Computation 2(3), 1995, 221-248.
13. C.A. Coello Coello, D.A. Van Veldhuizen, G.B. Lamont, Evolutionary Algorithms for Solving Multi-Objective Problems, Kluwer Academic Publishers, 2002
14. L. M. de Campos, J. A. Gàmez, and S. Moral. Partial abductive inference in bayesian belief networks using a genetic algorithm. Pattern Recogn. Lett., 20(11-13):1211-1217, 1999.