Introduction - If you have any usage issues, please Google them yourself
The constrained discrete optimization (CDO) is transfor med into a nonlinear constrained non-negative integer
programming (CNIP) which can be solved by the proposed discrete differential evolution (DDE) algorithm that adopts several
improvements such as the chaotic initialization of a population, the double-scheme mutation, and the integrating operator with
stochastic perturbation. Aiming at the nonlinear constraints, th e calculating approaches for the base penalty and the formula f or the
base function of continuous mapping are carried out, and self-adaptive penalty factors based on these notions for handling cons traints
are presented. It is studied that a novel measure, termed as a quasi re-averaging gene distance for a population, is employed t o depict
the diversity of the population and chaotic immigration operato rs depending on this measure a nd the probability are implemented to
preserve the population diversity. Orientating constrained engineering optimizati