Democratic Optimization for Discrete and Continuous Systems

摘要

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.