Sung Jinmo, Jeong Bongju
Department of Information & Industrial Engineering, Yonsei University, 50 Yonsei-Ro, Seodaemaun-gu, Seoul 120-749, Republic of Korea.
ScientificWorldJournal. 2014 Feb 17;2014:313767. doi: 10.1155/2014/313767. eCollection 2014.
Traveling sales man problem with precedence constraints is one of the most notorious problems in terms of the efficiency of its solution approach, even though it has very wide range of industrial applications. We propose a new evolutionary algorithm to efficiently obtain good solutions by improving the search process. Our genetic operators guarantee the feasibility of solutions over the generations of population, which significantly improves the computational efficiency even when it is combined with our flexible adaptive searching strategy. The efficiency of the algorithm is investigated by computational experiments.
带有优先级约束的旅行商问题，就其求解方法的效率而言，是最臭名昭著的问题之一，尽管它在工业上有非常广泛的应用。我们提出一种新的进化算法，通过改进搜索过程来高效地获得良好的解决方案。我们的遗传算子保证了种群代际间解决方案的可行性，即使与我们灵活的自适应搜索策略相结合，也能显著提高计算效率。通过计算实验对该算法的效率进行了研究。
