Siting Recycling Drop-off Stations in Urban Area by Genetic Algorithm-based Fuzzy Multiobjective Nonlinear Integer Programming Modeling


Due to the rapid depletion of landfill space and the time-consuming process for siting and building new municipal incinerators, solid waste management strategies have to be reorganized in light of the success of recycling, recovery and reuse of secondary materials. Effective planning of solid waste recycling programs, however, is currently a substantial challenge in many solid waste management systems, One of such efforts is how to effectively allocate the recycling drop-off stations with appropriate size in the solid waste collection network to maximize the recycling achievement with minimum expense. This paper illustrates a new approach with a view to optimizing siting and routing aspects using a fuzzy multiobjective nonlinear integer programming model as a means that is particularly solved by a genetic algorithm. The case study, based on one of the administrative districts in the city of Kaohsiung in Taiwan, presents the application potential of such a planning methodology.