Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/143723
Title: OPTIMAL ALLOCATION AND ROUTING FOR WASTE COLLECTION: CASE STUDY IN SINGAPORE
Authors: Xue Weijian
Keywords: GIS, spatial optimisation, linear programming, ant colony optimisation, waste collection, Singapore
Issue Date: 2015
Citation: Xue Weijian (2015). OPTIMAL ALLOCATION AND ROUTING FOR WASTE COLLECTION: CASE STUDY IN SINGAPORE. ScholarBank@NUS Repository.
Abstract: This thesis addresses two operational questions that waste collectors face on a day-to-day basis: where to send their waste and which route to take. Operations research has been crucial in producing tools to make data-driven decisions on such matters. This thesis contributes to this effort by proposing a two-phase allocation and routing model for waste collection, particularly in a city where there is heavily reliance on incineration for waste disposal. The allocation model determined how incineration capacities should be spatially distributed to waste generation points in a study area, so as to minimise collection costs by capitalising on the volume reduction capability of waste incineration. The model was solved using linear programming, and is the first-of-its-kind to be proposed. After which, the routing model determined an optimal route for waste transportation between a waste generation point and its allocated plant. The route was determined by a multi-objective optimisation of three factors: cost, accident risk and population exposure. It was solved using a heuristics method, the ant colony optimisation (ACO), which was modified to enhance its performance over conventional algorithms. The efficacies of both models have been shown using the implementation on Singapore as a case study, where there have been burgeoning amounts of waste being produced and increasing occurrence of accidents involving heavy vehicles. The results showed potential in producing a more cost-effective and safe waste collection regime in Singapore. The modified ACO also proved to be effective in providing a satisfactory global search for solutions and convergence to an optimal one within an acceptable amount of time.
URI: http://scholarbank.nus.edu.sg/handle/10635/143723
Appears in Collections:Bachelor's Theses (Restricted)

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