A review of multi-criteria optimization techniques for agricultural land use allocation

被引:110
|
作者
Kaim, Andrea [1 ]
Cord, Anna F. [1 ]
Volk, Martin [1 ]
机构
[1] UFZ Helmholtz Ctr Environm Res, Dept Computat Landscape Ecol, Permoserstr 15, D-04318 Leipzig, Germany
关键词
Agricultural land use allocation; Multi-criteria decision analysis (MCDA); Multi-criteria optimization; Stakeholder integration; Trade-off analysis; Constraint handling; TRADE-OFF ANALYSIS; ECOSYSTEM SERVICES; MULTIOBJECTIVE OPTIMIZATION; GENETIC ALGORITHM; DIFFERENTIAL EVOLUTION; DECISION-SUPPORT; BIODIVERSITY; CONSERVATION; MANAGEMENT; FRAMEWORK;
D O I
10.1016/j.envsoft.2018.03.031
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Optimal land use allocation with the intention of ecosystem services provision and biodiversity conservation is one of the key challenges in agricultural management. Optimization techniques have been especially prevalent for solving land use problems; however, there is no guideline supporting the selection of an appropriate method. To enhance the applicability of optimization techniques for real-world case studies, this study provides an overview of optimization methods used for targeting land use decisions in agricultural areas. We explore their relative abilities for the integration of stakeholders and the identification of ecosystem service trade-offs since these are especially pertinent to land use planners. Finally, we provide recommendations for the use of the different optimization methods. For example, scalarization methods (e.g., reference point methods, tabu search) are particularly useful for a priori or interactive stakeholder integration; whereas Pareto-based approaches (e.g., evolutionary algorithms) are appropriate for trade-off analyses and a posteriori stakeholder involvement. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:79 / 93
页数:15
相关论文
共 50 条
  • [1] Multi-criteria techniques integrated in GIS applied for land use allocation problems
    Carsjens, GJ
    vanderKnaap, WGM
    GEOGRAPHICAL INFORMATION - FROM RESEARCH TO APPLICATION THROUGH COOPERATION, VOLS 1 AND 2, 1996, : 575 - 578
  • [2] Multi-criteria optimization of the arable land use
    Ulez'ko, A., V
    Demidov, P., V
    6TH INTERNATIONAL CONFERENCE ON AGRIPRODUCTS PROCESSING AND FARMING, 2020, 422
  • [3] The taxation of agricultural land with the use of multi-criteria analysis
    Siroky, Jan
    Krajcova, Jirina
    Hakalova, Jana
    AGRICULTURAL ECONOMICS-ZEMEDELSKA EKONOMIKA, 2016, 62 (05): : 197 - 204
  • [4] Application of Multi-Criteria Decision-Making in Land Evaluation of Agricultural Land Use
    Jozi, Seyed Ali
    Ebadzadeh, Farkhondeh
    JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING, 2014, 42 (02) : 363 - 371
  • [5] Application of Multi-Criteria Decision-Making in Land Evaluation of Agricultural Land Use
    Seyed Ali Jozi
    Farkhondeh Ebadzadeh
    Journal of the Indian Society of Remote Sensing, 2014, 42 : 363 - 371
  • [6] ASSET ALLOCATION WITH MULTI-CRITERIA DECISION MAKING TECHNIQUES
    Ozcalici M.
    Decision Making: Applications in Management and Engineering, 2022, 5 (02): : 78 - 119
  • [7] Multi-criteria decision making methods to address rural land allocation problems: A systematic review
    Gebre, Sintayehu Legesse
    Cattrysse, Dirk
    Alemayehu, Esayas
    Van Orshoven, Jos
    INTERNATIONAL SOIL AND WATER CONSERVATION RESEARCH, 2021, 9 (04) : 490 - 501
  • [8] Maintenance applications of multi-criteria optimization: A review
    Syan, Chanan S.
    Ramsoobag, Geeta
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2019, 190
  • [9] A MULTI-CRITERIA EVALUATION APPROACH TO ACCESS AGRICULTURAL LAND USE POTENTIAL ON THE LOESS PLATEAU OF CHINA
    Ye, Jiansheng
    Li, Fengmin
    Sun, Guojun
    Chen, Yaxiong
    Mou, Yanling
    INTELLIGENT AUTOMATION AND SOFT COMPUTING, 2010, 16 (06): : 891 - 901
  • [10] A multi-criteria land suitability assessment of field allocation decisions for switchgrass
    Griffel, L. Michael
    Toba, Ange-Lionel
    Paudel, Rajiv
    Lin, Yingqian
    Hartley, Damon S.
    Langholtz, Matthew
    ECOLOGICAL INDICATORS, 2022, 136