In this research we consider the Vehicle Routing Problemwith Loading Constraints (VRPLC). We attempt tointegrate the classical Vehicle Routing Problem (VRP)and Container Loading Problem (CLP), which are NPhardproblem respectively, into a single model. Theobjectives are to minimize the traveling costs and tomaximize the utilization of the container space. In thiscase, all cargos of a customer in the container should belocated next to each other and all cargos can be unloadedwithout moving cargos for other customers. Thus, thecargos of last visited customers should be packed first andthose for earlier visited customers should be loaded last.Accordingly, the VRPLC contains complex vehiclerouting and packing constraints. To solve the problem, wedevelop a Genetic Algorithms Heuristic methodconsidering cross-over and mutation operations. Based onthe GA algorithms, we finally develop a softwareprototype that helps users to manage packing process in3D visualization. Finally, we provide a numericalexample to show how the software works.