Building "just in time" distribution systems to improve the delivery efficiency requires solving at least several tens to hundred cities time-constraint Traveling Salesman Problems (TSP) within interactive response time, with practicable optimality. To meet these requirements, a Locally-Selfish-gene Tolerant Dynamic Control GA is proposed. Here, each gene of an individual satisfies only its constraints selfishly, disregarding the constraints of other genes in the same individual. Further, to some extent, even individuals that violate constraints can survive over generations and are given the chance of improvement. Moreover, evolution is promoted by dynamically changing the degree of the tolerance and GA operations. Our experiment proved that this method provides expertlevel solutions for several tens to hundred cities time constraint TSPs within a few seconds.