Sustainable Optimization of the Solid Wastes Management During Fifa-2022 in Qatar

Qatar is one of the most developed countries worldwide that became an ideal destination for residence, thereby leading to an increase in the population. This resulted in a consequent increase in solid waste generation in the country, which is bound to overload the waste management system. The present thesis proposes certain models and approaches for selecting the location of Qatar’s waste transfer stations using different optimization tools. A mathematical model was developed to describe four different configurations that attempt to optimize the current and future system of waste management: (i) the addition of new permanent waste transfer facilities that accept multiple types of waste; (ii) the addition of new temporary waste transfer stations facilities that accept one type of waste; (iii) the selection of new permanent waste transfer stations regardless of whether it is an existing or potential site and it is capable of handling multiple types of waste; and (iv) the selection of new permanent waste transfer stations that will be capable of handling multiple types of waste and temporary waste transfer stations that will handle one type of waste, regardless whether they are an existing or potential site. Among the considered configurations, the results showed that configuration model 4 works the best. It selects three out of five existing waste transfer stations, three potential permanent sites, and four temporary waste transfer stations at the minimum overall cost compared to the outcomes provided by the other three models. The validity of the results of the model was confirmed even by the analytical hierarchy process (AHP) method, which provided results that match the mathematical model’s outcomes up to 90%. The novelty of the proposed models includes utilizing multiple optimization tools for selecting the locations of solid waste transfer stations in Qatar and introducing the employment of temporary transfer stations for the first time.