This essay discusses the nonverbal communication between east and west culture with the help of applying contrastive and analytic method. It aims at arousing people's awareness of nonverbal communication in intercultural communication, enhancing their intercultural communicative competence accordingly, and finally eliminating cultural misunderstanding and fraction.

Abstract. The traditional ant colony optimization (ACO) had defects in long searching time and convergence in local optima solution. To solve the problem, a hybrid ant colony optimization algorithm (HACO) was proposed in this paper. Two modes in HACO are defined that are DefaultModel and EliteModel. In order to search the optimum result, the two modes will be automatically switched in this algorithm. It also use the parallel calculation model of MapReduce to loop iteration part of ACO and deploy it on the Hadoop cloud computing platform. Finally, simulation results validate the proposed approach on the traveling salesman problem.

An improved evolutionary algorithm (SCAGA) is proposed in this paper. The algorithm is based on new population initialization method and genetic operator. SCAGA adopts the crossover probability and mutation probability that vary with the increase of evolution generation in order to control genetic operations in an effective range. Meanwhile, SCAGA presents a new crossover strategy that restricts the cross of the chromosomes to some extent to protect good genes schema. The schema theorem is employed in the algorithm to analyze the working mechanism of SCAGA. According to experiment results for test functions and TSP problems, SCAGA is effective.

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