For successful application of Genetic Algorithm (GA) to combinatorial optimization problems, a suitable distance between two solutions, or phenotypes is useful to estimate the problem landscape. This paper presents a general distance function between two phenotypes. The phenotypic distance is defined by the least Hamming distance between isomorphic genotypes. Therefore, it is convenient to analyze and control the behavior of genotypes in the search space. By using the phenotypic distance, this paper proposes a new crossover technique named Harmonic Crossover. Because a new child is located between two parents in the problem space, the character of parents is preserved with the Harmonic Crossover. Furthermore, this paper presents a hybrid algorithm which combines GA with a conventional local search algorithm. The effectiveness of the proposed techniques are also confirmed on the traveling salesman problems.