DescriptionAn optimization model is proposed to find out the best waste to energy (WtE) technology combination and municipal solid waste (MSW) disposal scenario for a disadvantaged community. Three major types of waste streams and three mainstream WtE technologies are of interest there; waste streams are paper waste, plastic waste, and organic waste; WtE techniques are incineration, pyrolysis/gasification, and anaerobic digestion (AD). Whilst other possible renewable energies such as solar resource are considered as an option to make profit and operate the community cleanly. In this study, firstly, forecasts of waste generation and population of this region are performed on a ten-year scale using method called a fuzzy grey model GM (1, 1). The prediction of waste generated in studied region is the feedstock of WtE technologies to produce energy. In addition, the compositions of different waste streams are calculated, assuming waste materials are collected and classified and then could be applied to optimization model directly. The problem arises that for disadvantaged communities to fully utilize the waste land there and recover energy from waste to transfer it into clean one, a multi-objective optimization model is formulated to maximize the profit and minimize the carbon emission of the WtE industries while satisfying the energy consumption. A case study of community in Los Angeles. is performed after methodology was modeled; results show that the installation of WtE plants and solar panels will make this community self-sustaining and accomplish a positive net profit after ten-year run. This research is a starting point of one new part of a whole simulation platform called Smart City. Aiming at planning for a clean and efficient community, this research mainly finds the possibility of transferring a disadvantaged community and recovering waste energy as much as possible in an optimal setting. Some details of the problem are not addressed, but this study still gives out some possible future work directions.