An improved procedure to implement NSGA-III in coordinate waste management for urban agglomeration

With the growth of urbanization in countries globally, large cities have often formed clusters of urban agglomerations in metropolitan areas. The coordinated management of regional solid waste produced by such urban agglomeration poses a typical high-dimensional, multi-objective optimization issue. This paper aims to introduce a procedure to implement the third-generation genetic algorithm (NSGA-III), an established multi-objective genetic algorithm based on non-dominated sorting mechanisms, for the purpose of evaluating environmental and economic benefits simultaneously while seeking the optimal solutions for coordinated management among multiple recycling centres. In this study, two series of scenarios were abstracted from scrap tire recycling, representing linear calculation and nonlinear calculation cases separately. Several improvements were made to the originally published NSGA-III procedure that solve the problem of non-convergence for hypervolumes of the output. Through comparisons of calculation results, an improved procedure is suggested and shown to have improved performance.