Effective planning of solid-waste recycling programs is a substantial challenge to the current solid-waste management systems in Taiwan. Due to the rapid depletion of landfill space and the continuing delay in construction programs of municipal incinerators, solid-waste management strategies have to be reorganized in light of the success of recycling, recovery, and reuse of secondary materials. One of these efforts is how to effectively allocate recycling drop-off stations of appropriate size and how to design efficient collection-vehicle routing and scheduling programs in the solid waste collection network. This management strategy is particularly important in the privatized system with recycling containers and material recovery facilities (MRFs) owned by one agency. This research seeks multiobjective evaluation of the trade-off between the number and size of drop-off stations, the population covered in the service network, the average walking distance to dropoff stations by the population, and the distance traveled by collection vehicles. it also illustrates the use of the multiobjective nonlinear mixed integer programming model to achieve such goals that are solved by the genetic algorithms (GA) in a geographical information system (GIS) platform. The case study shows the application potential of such a methodology in the city of Kaohsiung in Taiwan.