2021 Volume 64 Pages 71-100
This research focuses on the three objects of using heat energy generated by incineration (maximizing the amount of heat), minimizing total waste weighted distances, and maximizing total population density weighted distances for determining allocations and locations of general waste incineration facilities. For these objectives, we proposed the Multi-objective Optimization with Voronoi diagram and Genetic Algorithm (MOVGA), which has the XY coordinates of the Voronoi seeds and the ID of the facility locations as genes. As for the maximization of the amount of generated heat, we predicted the amount by using the regression equation of multiple regression analysis, and formulated it as the set partitioning problem (SPP) to maximize the prediction value. As for the minimization of the total waste weighted distances, we formulated it as the P-median problem to reduce the environmental load. As for the maximization of the total population density weighted distances, we formulated it as the P-median problem to keep away incineration facilities from densely populated areas. And also, we considered reducing the number of facilities when optimizing. To verify the validity of the MOVGA method, we conducted the case study on Chiba northwest bay area (Ichikawa city, Funabashi city, Narashino city and Urayasu city). As a result of the research, we obtained the approximate solution that can cover 2,788 [households/year] in terms of apartments, with the calorific value increased by 2.275E+11 [kJ/year] (6% increase compared to 2015) under the conditions of 4 facilities (decreased 1 facility compared to the 2015 year). From the research results, we verified that the MOVGA is effective in effectively using thermal energy and reducing the number of facilities in the target area.