The chapter introduces two examples of bio-inspired algorithm for traveling sales-man problems and its extended version. The first algorithm, named ant colony optimization (ACO) which is designed inspired by the natural ants' behavior, is a novel method to deal with TSPs. The experimental results prove the performance of ACO approach, which is feasible to solve TSP instances as well as the traditional method. The research results about the self-adaptive parameters of ACO are presented in the chapter, which indicates how to set an optimal ACO algorithm for different TSPs. Another algorithm is genetic algorithm, which is used to solve generalized traveling sales-man problem (GTSP) that is one extended style of TSPs. The best-so-far genetic algorithm for GTSP is introduced in the final subsection. Bio-inspired algorithms are the feasible methods for TSPs, and can attain better performance with the modified setting like self-adaptive parameters and hybrid coding, which are described in the chapter.