In some cases, there are some special requirements for the vehicle routing problem. Personnel or goods geographically
scattered, should be delivered simultaneously to an assigned place by a fleet of vehicles as soon as possible. In this case
the objective is to minimize the distance of the longest route among all sub-routes. An improved genetic algorithm was
adopted to solve these problems. Each customer has a unique integer identifier and the chromosome is defined as a string
of integers. Initial routes are constructed randomly, and then standard proportional selection incorporating elitist is
chosen to guarantee the best member survives. New crossover and 2-exchange mutation is adopted to increase the
diversity of group. The algorithm was implemented and tested on some instances. The results demonstrate the
effectiveness of the method.