Abstract
In this article, we propose a new scatter-search-based learning algorithm to train feed-forward neural networks. The algorithm also incorporates elements of tabu search. We describe the elements of the new approach and test the new learning algorithm on a series of classification problems. The test results demonstrate that the algorithm is significantly superior to several implementations of back-propagation.
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Glover, F. (1977). “Heuristics for Integer Programming Using Surrogate Constraints.” Decision Sciences 8(1) (January), 156–166.
Glover, F. (1989). “Tabu Search, Part I.” ORSA Journal on Computing 1(3), 190–206.
Glover, F. (1990) “Tabu Search, Part II.” ORSA Journal on Computing 2(1), 4–32.
Glover, F. (1994). “Genetic Algorithms and Scatter Search: Unsuspected Potentials.” Statistics and Computing 4, 131–140.
Glover, F. (1996). “Tabu Search and Adaptive Memory Programming—Advances, Applications and Challenges.” To appear in Barr, Helgason, and Kennington, Interfaces in Computers Science and Operations Research. Boston: Kluwer.
Glover, F., and M. Laguna. “Tabu Search.” In Collin Reeves (Ed.), Modern Heuristic Techniques for Combinatorial Optimization. Blackwell Publishers. pp. 60–150.
Haykin, S. (1994). Neural Networks: A Comprehensive Foundation. New York: Macmillan College.
Mangasarian, O.L. (1993) “Mathematical Programming in Neural Networks.” ORSA Journal on Computing 5(4) (Fall), 349–360.
Nowicki, E., and C. Smutnicki. (1995). “The Flow Shop with Parallel Machine: A Taboo Search Approach.” Report ICT PRE 30/95, Technical University of Wroclaw.
Nowicki, E., and C. Smjtnicki. (1996a). “A Fast Taboo Search Algorithm for the Job Shop.” Management Science 4–2(6), 797–813.
Nowicki, E., and C. Smutnicki. (1996b). “A Fast Tabu Search Algorithm for the Permutation Flow Shop.” European Journal of Oper. Res. 91(1), 160–175.
Patuwo, E., M.Y. Hu, and M.S. Hung. (1993). “Two-Group Classification Using Neural Networks.” Decision Sciences 24(4), 825–844.
Roy, A., S. Govil, and R. Miranda (1995). “An Algorithm to Generate Radial Basis (RBF)-like Nets for Classification Problems.” Neural Networks 8(1), 179–201.
Rummelhart, D.E., B. Widrow, and M.A. Lehr. (1994). “The Basic Ideas in Neural Networks.” Communications of the ACM 37(3) (March), 87–92.
Rummelhart, D.E., G.E. Williams, and R.J Williams. (1986) “Learning Internal Representations by Error Propagation.” Parallel Distributed Processing 1, pp. 318–362. Cambridge, MA: MIT Press.
Subramanian, V., and M.S. Hung.(1993). “A GRG2-Based System for Training Neural Networks: Design and Computational Experience,” ORSA Journal on Computing 5(4) (Fall), 386–394.
Wasserman, P.D. (1989). Neural Computing-Theory and Practice. New York: Van Nostrand Reinhold.
Widrow, B., D.E. Rummelhart, and M.A. Lehr. (1994). “Neural Networks: Applications in Industry, Business and Science.” Communications of the ACM, 37(3) (March), 93–105.
Xu, J. and J.P. Kelly. (1996). “A New Network-Flow-Based Tabu Search Heuristic for the Vehicle Routing Problem.” Transportation Science 30(4), 1–15.
Xu, J., S.Y. Chiu, and F. Gover. (1996). “Probabilistic Tabu Search for Telecommunications Network Design.” Journal of Combinatorial Optimization.
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Kelly, J.P., Rangaswamy, B. & Xu, J. A scatter-search-based learning algorithm for neural network training. J Heuristics 2, 129–146 (1996). https://doi.org/10.1007/BF00247209
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DOI: https://doi.org/10.1007/BF00247209