Multi-objective optimization of allocations and locations of incineration facilities with Voronoi diagram and genetic algorithm: Case study of northwest bay area in Chiba prefecture

This research focuses on the two purposes of maximizing the amount of heat generated by incineration and minimizing the collection distance of waste, in determining allocations and locations of general waste incineration facilities as a case study of Chiba northwest bay area. For these purposes, we propose the multi-objective optimization with Voronoi diagram and genetic algorithm (MOVGA). As for the maximization of the amount of generated heat, we predict the amount by using regression equation of multiple linear regression analysis and formulate it as the set partitioning problem (SPP) to maximize the prediction value. As for the minimization of waste collection distances, we formulate it as the multi-Weber problem. To solve these two problems, we use MOVGA, which has the seeds of the Voronoi diagram as a gene. As a result of the survey using data of 2015 year of Chiba northwest bay area, in the case of 3 facilities it was found that the calorific value increased enough to cover the power of 4,205 households (converted to housing complex) per year despite the increase of 3% t-km per year.