A Hesitant Probabilistic Fuzzy Multi-Criteria Group Decision-Making Framework for Urban Land Consolidation in China

Urban land consolidation (ULC) is a technique used globally for urbanization planning. Selecting a suitable area for ULC becomes the most feasible plan for urban redevelopment in China, which can be regarded as a complex multi-criteria group decision-making problem. In this article, a hesitant probabilistic fuzzy multi-criteria group decision-making framework is proposed to solve the site selection problem of ULC. In the framework, hesitant probabilistic fuzzy set are used to represent the evaluation information provided by decision makers. Furthermore, the framework utilizes a new method based on entropy and the analytic hierarchy process for determining weights. The hesitant probabilistic fuzzy combined weighted logarithmic averaging distance (HPFCWLAD) measure is then introduced for sorting the alternatives found by the system. To validate the proposed framework, a site selection case of ULC including five alternatives in Hangzhou is investigated. The effectiveness and stability of the framework is proved through a comparative analysis.

[1]  Jing Wang,et al.  Urban–Rural Construction Land Replacement for More Sustainable Land Use and Regional Development in China: Policies and Practices , 2019, Land.

[2]  Zengxiang Zhang,et al.  Assessing the Potential of Rural Settlement Land Consolidation in China: A Method Based on Comprehensive Evaluation of Restricted Factors , 2018, Sustainability.

[3]  Jian Li,et al.  Multi-criteria decision-making method based on dominance degree and BWM with probabilistic hesitant fuzzy information , 2018, International Journal of Machine Learning and Cybernetics.

[4]  Zeshui Xu,et al.  A Novel Comparison of Probabilistic Hesitant Fuzzy Elements in Multi-Criteria Decision Making , 2018, Symmetry.

[5]  Huayou Chen,et al.  Generalized logarithmic proportional averaging operators and their applications to group decision making , 2012, Knowl. Based Syst..

[6]  José M. Merigó,et al.  Logarithmic aggregation operators and distance measures , 2018, Int. J. Intell. Syst..

[7]  Zeshui Xu,et al.  Entropy Measures for Probabilistic Hesitant Fuzzy Information , 2019, IEEE Access.

[8]  F. Burel,et al.  Can urban consolidation limit local biodiversity erosion? Responses from carabid beetle and spider assemblages in Western France , 2014, Urban Ecosystems.

[9]  Zeshui Xu,et al.  The Strategy Selection Problem on Artificial Intelligence With an Integrated VIKOR and AHP Method Under Probabilistic Dual Hesitant Fuzzy Information , 2019, IEEE Access.

[10]  Huimin Lu,et al.  Introduction to the special section on Artificial Intelligence and Computer Vision , 2017, Comput. Electr. Eng..

[11]  Yong-sheng Wang,et al.  The Challenges and Strategies of Food Security under Rapid Urbanization in China , 2019, Sustainability.

[12]  Gregory Brown,et al.  An evaluation of contemporary China’s land use policy – The Link Policy: A case study from Ezhou, Hubei Province , 2020 .

[13]  José Portela,et al.  A social approach to land consolidation schemes: A Portuguese case study: the Valença Project , 1996 .

[14]  W. Yin,et al.  From urban sprawl to land consolidation in suburban Shanghai under the backdrop of increasing versus decreasing balance policy: A perspective of property rights transfer , 2017 .

[15]  Shouzhen Zeng,et al.  Single-Valued Neutrosophic Linguistic Logarithmic Weighted Distance Measures and Their Application to Supplier Selection of Fresh Aquatic Products , 2020 .

[16]  Yunhao Chen,et al.  How feasible is Regional Integration for reconciling land use conflicts across the urban-rural interface? Evidence from Beijing-Tianjin-Hebei metropolitan region in China , 2020, Land Use Policy.

[17]  Ding Chengri.  The integration of transportation and land use: the new urbanism and smart growth , 2005 .

[18]  Qin Wang,et al.  Probabilistic multi-criteria assessment of renewable micro-generation technologies in households , 2019, Journal of Cleaner Production.

[19]  Zhenrong Yu,et al.  Possibilities and requirements for introducing agri-environment measures in land consolidation projects in China, evidence from ecosystem services and farmers' attitudes. , 2019, The Science of the total environment.

[20]  J. Ren,et al.  Ecological environment quality assessment based on remote sensing data for land consolidation , 2019, Journal of Cleaner Production.

[21]  Tianzhu Zhang,et al.  Land Consolidation Design Based on an Evaluation of Ecological Sensitivity , 2018, Sustainability.

[22]  Tayfun Cay,et al.  Comparison of designed different land reallocation models in land consolidation: A case study in Konya/Turkey , 2015, Comput. Electron. Agric..

[23]  Zeshui Xu,et al.  Uncertainty Measures for Hesitant Fuzzy Information , 2015, Int. J. Intell. Syst..

[24]  Jian Li,et al.  Consensus Building for Probabilistic Hesitant Fuzzy Preference Relations with Expected Additive Consistency , 2018, Int. J. Fuzzy Syst..

[25]  Vicenç Torra,et al.  Hesitant fuzzy sets , 2010, Int. J. Intell. Syst..

[26]  Kuo-Liang Lin,et al.  Determining key ecological indicators for urban land consolidation , 2010 .

[27]  Zeshui Xu,et al.  Multi-attribute decision making methods based on reference ideal theory with probabilistic hesitant information , 2019, Expert Syst. Appl..

[28]  Jian Li,et al.  Multi-criteria decision-making with probabilistic hesitant fuzzy information based on expected multiplicative consistency , 2018, Neural Computing and Applications.

[29]  Zeshui Xu,et al.  Operations and integrations of probabilistic hesitant fuzzy information in decision making , 2017, Inf. Fusion.

[30]  Zeshui Xu,et al.  Consensus building with a group of decision makers under the hesitant probabilistic fuzzy environment , 2016, Fuzzy Optimization and Decision Making.

[31]  Xin Gao,et al.  How regional economic integration influence on urban land use efficiency？ A case study of Wuhan metropolitan area, China , 2020 .

[32]  Zeshui Xu,et al.  Distance and similarity measures for hesitant fuzzy sets , 2011, Inf. Sci..

[33]  Zeshui Xu,et al.  An interactive approach to probabilistic hesitant fuzzy multi-attribute group decision making with incomplete weight information , 2017, J. Intell. Fuzzy Syst..

[34]  Zeshui Xu,et al.  New Correlation Coefficients Between Probabilistic Hesitant Fuzzy Sets and Their Applications in Cluster Analysis , 2018, Int. J. Fuzzy Syst..

[35]  A. Tezcan,et al.  A multi-criteria model for land valuation in the land consolidation , 2020, Land Use Policy.

[36]  B. Tang,et al.  Institutional change and diversity in the transfer of land development rights in China: The case of Chengdu , 2020, Urban Studies.

[37]  Jian Li,et al.  Multi-criteria Outranking Methods with Hesitant Probabilistic Fuzzy Sets , 2017, Cognitive Computation.

[38]  Zeshui Xu,et al.  A Dynamic Reference Point Method for Emergency Response Under Hesitant Probabilistic Fuzzy Environment , 2017, Int. J. Fuzzy Syst..

[39]  Shouzhen Zeng,et al.  A Probabilistic Linguistic Multiple Attribute Decision Making Based on a New Correlation Coefficient Method and its Application in Hospital Assessment , 2020, Mathematics.

[40]  Peter Wyatt,et al.  The development of a property information system for valuation using a geographical information system (GIS) , 1996 .

[41]  Xingsen Li,et al.  A Correlation-Based TOPSIS Method for Multiple Attribute Decision Making with Single-Valued Neutrosophic Information , 2020, Int. J. Inf. Technol. Decis. Mak..

[42]  Zlatica Muchová,et al.  Prioritization and Evaluation of Land Consolidation Projects—Žitava River Basin in a Slovakian Case , 2019, Sustainability.