摘要：As a new promising crossover method, multiple crossovers per couple (MCPC) deserves specialattention in evolutionary computing field. Allowing multiple crossovers per couple on a selected pair ofparents provided an extra benefit in processing time and similar quality of solutions when contrasted againstthe conventional single crossover per couple approach (SCPC). These results, were confirmed whenoptimising classic testing functions and harder (non-linear, non-separable) functions.Despite these benefits, due to a reinforcement of selective pressure, MCPC showed in some casesan undesirable premature convergence effect. In order to face this problem, the present paper attemptsto control the number of crossovers, and offspring, allowed to the mating pair in a self-adaptive manner.Self-adaptation of parameters is a central feature of evolutionary strategies, another class ofevolutionary algorithms, which simultaneously apply evolutionary principles on the search space ofobject variables and on strategy parameters. In other words, parameter values are also submitted to theevolutionary process. This approach can be also applied to genetic algorithms.In the case of MCPC, the number of crossovers allowed to a selected couple is a key parameter andconsequently self-adaptation is achieved by adding to the chromosome structure "labels" describing thenumber of crossover allowed to each individual. Labels, which are bit strings, also undergo crossover andmutation and consequently evolve together with the individual. During the stages of the evolution process, it isexpected that the algorithm will return the number of crossovers for which the current population exhibits abetter behaviour
