Abstract

For the sake of solving the optimization problem of urban waste collection and transportation in China, a priority considered green vehicle routing problem (PCGVRP) model in a waste management system is constructed in this paper, and specific algorithms are designed to solve the model. We pay particular concern to the possibility of immediate waste collection services for high-priority waste bins, e.g., those containing hospital or medical waste, because the harmful waste needs to be collected immediately. Otherwise, these may cause dangerous or negative effects. From the perspective of environmental protection, the proposed PCGVRP model considers both greenhouse gas (GHG) emission costs and conventional waste management costs. Waste filling level (WFL) is considered with the deployment of sensors on waste bins to realize dynamic routes instead of fixed routes, so that the economy and efficiency of waste collection and transportation can be improved. The optimal solution is obtained by a local search hybrid algorithm (LSHA), that is, the initial optimal solution is obtained by particle swarm optimization (PSO) and then a local search is performed on the initial optimal solution, which will be optimized by a simulated annealing (SA) algorithm by virtue of the global search capability. Several instances are selected from the database of capacitated vehicle routing problem (CVRP) so as to test and verify the effectiveness of the proposed LSHA algorithm. In addition, to obtain credible results and conclusions, a case using data about waste collection and transportation is employed to verify the PCGVRP model, and the effectiveness and practicability of the model was tested by setting a series of values of bins’ number with high priority and WFLs. The results show that (1) the proposed model can achieve a 42.3% reduction of negative effect compared with the traditional one; (2) a certain value of WFL between 60% and 80% can realize high efficiency of the waste collection and transportation; and (3) the best specific value of WFL is determined by the number of waste bins with high priority. Finally, some constructive propositions are put forward for the Environmental Protection Administration and waste management institutions based on these conclusions.

Highlights

  • Municipal solid waste (MSW) management is regarded as a challenging matter for contemporary cities [1,2] due to quick growth in the amount of waste, high waste collection costs [3], limited treatment capacities [4] and environmental problems [5]

  • The results of particle swarm optimization (PSO) and the proposed algorithm are compared in Table 8, including total distance, total greenhouse gas (GHG) emissions and total costs

  • By considering specific waste bins with high priority and filling levels of general waste bins, we study the impact of different numbers of waste bins with high priority and Waste filling level (WFL) on the negative effect, costs, the percentage of collected waste and vehicle utilization rate

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Summary

Introduction

Municipal solid waste (MSW) management is regarded as a challenging matter for contemporary cities [1,2] due to quick growth in the amount of waste, high waste collection costs [3], limited treatment capacities [4] and environmental problems [5]. Public Health 2020, 17, 4963; doi:10.3390/ijerph17144963 www.mdpi.com/journal/ijerph

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