Abstract
A novel strategy for finding optimal solutions to complex problems with many competing requirements is proposed. It consists in a simultaneous optimization of the energy, cost or fitness function of the system itself, and of sub-systems of all sizes with an appropriate weight function. For various travelling salesman problems and spin glasses as well as for an example of a continuous-valued system (the optical multilayer problem) the corresponding Monte Carlo algorithm is shown to yield results superior to those obtained by previous optimization techniques.
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© 1996 Springer-Verlag Berlin Heidelberg
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Dittes, FM. (1996). Democratic optimization for discrete and continuous systems. In: Voigt, HM., Ebeling, W., Rechenberg, I., Schwefel, HP. (eds) Parallel Problem Solving from Nature — PPSN IV. PPSN 1996. Lecture Notes in Computer Science, vol 1141. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61723-X_1028
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DOI: https://doi.org/10.1007/3-540-61723-X_1028
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