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, re covery and reuse of secondary materials. Effective planning of solid waste recycling programs, however, is currently a substantial challenge in many s olid waste management systems, One of such efforts is how to effectively al locate the recycling drop-off stations with appropriate size in the solid w aste collection network to maximize the recycling achievement with minimum expense. This paper illustrates a new approach with a view to optimizing si ting and routing aspects using a fuzzy multiobjective nonlinear integer pro gramming model as a means that is particularly solved by a genetic algorith m. The case study, based on one of the administrative districts in the city of Kaohsiung in Taiwan, presents the application potential of such a plann ing methodology. (C) 2000 Elsevier Science B.V. All rights reserved.