Optimization of site selection for construction and demolition waste recycling plant using genetic algorithm

With regard to the site selection of construction and demolition of waste recycling plants in China, an optimization model for the site selection of a recycling plant was constructed using a genetic algorithm, and an empirical study was conducted with Panyu and Nansha Districts of Guangzhou City as examples. The study shows that the optimal solution obtained on optimizing the site selection of a construction and demolition waste recycling plant using a genetic algorithm conforms to the actual investigation. The optimal solution using the genetic algorithm was obtained after only 200 iterations, at which point the fitness value converges at a stable value of 1.8 × 10−5, which proves the rationality and operability of the site-selection optimization model. However, given the slow evolutionary speed of the genetic algorithm, it is easy to fall into a local optimum. Thus, its improvement using a tabu algorithm is necessary. The research results can provide the government with a theoretical basis for the site selection of construction and demolition waste recycling plants.

[1]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[2]  Pablo Aragonés-Beltrán,et al.  An Analytic Network Process approach for siting a municipal solid waste plant in the Metropolitan Area of Valencia (Spain). , 2010, Journal of environmental management.

[3]  Godfrey C. Onwubolu,et al.  Emerging optimization techniques in production planning and control , 2002 .

[4]  Zhou Da.  The Research on Present Situation of China's Circular Economy Policy,Environment and the Orientation , 2010 .

[5]  Hongwei Liu,et al.  The Effect of Satisfaction on Loyalty in Consumption and Service Industry Based on Meta-analysis and It’s Algorithm , 2018, Wirel. Pers. Commun..

[6]  Chen Cheng,et al.  Application of GA and TS in Logistics Distribution Center Location and Routing Problem , 2007 .

[7]  K. Clemitshaw,et al.  Use of genetic algorithms to improve the solid waste collection service in an urban area. , 2015, Waste management.

[8]  M Zamorano,et al.  Methodology of Environmental Diagnosis for Construction and Demolition Waste Landfills: a Tool for Planning and Making Decisions , 2005, Environmental technology.

[9]  Weimin Wang,et al.  Applying multi-objective genetic algorithms in green building design optimization , 2005 .

[10]  Xie Tao,et al.  Evolutionary Algorithms of Multi-Objective Optimization Problems , 2003 .

[11]  Gongbing Bi,et al.  An image edge recognition approach based on multi-operator dynamic weight detection in virtual reality scenario , 2018, Cluster Computing.

[12]  Peng Xuya.  Establishment of optimization model for location of municipal solid waste transfer station and its application , 2006 .

[13]  Ioannis Giannikos,et al.  A multiobjective programming model for locating treatment sites and routing hazardous wastes , 1998 .

[14]  Nicolas Moussiopoulos,et al.  Assessing multiple criteria for the optimal location of a construction and demolition waste management facility , 2010 .

[15]  Tong Heng Lee,et al.  Evolutionary algorithms with dynamic population size and local exploration for multiobjective optimization , 2001, IEEE Trans. Evol. Comput..

[16]  Yujing Chen,et al.  Distinguishing investment changes in metro construction project based on a factor space algorithm , 2018, Cluster Computing.

[17]  Vera Susanne Rotter,et al.  Evaluation of the economic feasibility for the recycling of construction and demolition waste in China—The case of Chongqing , 2010 .

[18]  Horst A. Eiselt,et al.  Location analysis: A synthesis and survey , 2005, Eur. J. Oper. Res..

[19]  Yujing Chen,et al.  Knowledge Management of Web Financial Reporting in Human-Computer Interactive Perspective. , 2017 .

[20]  R. K. Ursem.  Multi-objective Optimization using Evolutionary Algorithms , 2009 .

[21]  Ren Ming-ming.  Undesirable Facility Location Problem using a Multi-objective Evolutionary Algorithm , 2007 .

[22]  Dong Wang,et al.  A Meta-analysis of Satisfaction-Loyalty Relationship in E-Commerce: Sample and Measurement Characteristics as Moderators , 2018, Wirel. Pers. Commun..

[23]  Junqiang Xia,et al.  Urban construction and demolition waste and landfill failure in Shenzhen, China. , 2017, Waste management.

[24]  Dong Wang,et al.  Efficiency optimization and simulation to manufacturing and service systems based on manufacturing technology Just-In-Time , 2018, Personal and Ubiquitous Computing.

[25]  QU Zhi-wei,et al.  The Location-Routing Problem in the Municipal Solid Waste Logistics System , 2005 .

[26]  Jianchang Lu,et al.  Selection of Cold Chain Logistics Distribution Center Location Based on Improved Genetic Algorithm , 2018 .

[27]  M R Khadivi,et al.  Solid waste facilities location using of analytical network process and data envelopment analysis approaches. , 2012, Waste management.

[28]  Dimitrios Komilis,et al.  A methodology to optimally site and design municipal solid waste transfer stations using binary programming , 2012 .

[29]  Yujing Chen,et al.  Cost-effectiveness analysis and evaluation of a ‘three-old’ reconstruction project based on smart system , 2017, Cluster Computing.

[30]  Luan Mao-tian,et al.  Fuzzy sets theory for multi-objective system and its application to site selection of municipal solid wastes landfill , 2004 .