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
  • [41] Correction to: Multi-criteria optimization in regression
    Mike G. Tsionas
    Annals of Operations Research, 2024, 332 (1-3) : 1157 - 1157
  • [42] Multi-criteria optimization for scalable bitstreams
    Lerouge, S
    Lambert, P
    Van de Walle, R
    VISUAL CONTENT PROCESSING AND REPRESENTATION, PROCEEDINGS, 2003, 2849 : 122 - 130
  • [43] MULTI-CRITERIA OPTIMIZATION IN SPACE MANAGEMENT
    Vucijak, Branko
    PROSTOR, 2007, 15 (01): : 109 - 117
  • [44] A theory of lexicographic multi-criteria optimization
    Rentmeesters, MJ
    Tsai, WK
    Lin, KJ
    SECOND IEEE INTERNATIONAL CONFERENCE ON ENGINEERING OF COMPLEX COMPUTER SYSTEMS: HELD JOINTLY WITH 6TH CSESAW, 4TH IEEE RTAW, AND SES'96, 1996, : 76 - 79
  • [45] Multi-criteria optimization of a hexapod machine
    Kübler, L
    Henninger, C
    Eberhard, P
    ADVANCES IN COMPUTATIONAL MULTIBODY SYSTEMS, 2005, 2 : 319 - 343
  • [46] Multi-Criteria Optimization of Bridge Management
    Wang Zeng-zhong
    Fan Li-chu
    Mark, Hastak
    ADVANCES IN CIVIL ENGINEERING, PTS 1-6, 2011, 255-260 : 4080 - +
  • [47] Multi-criteria optimization for seawater desalination
    Chamblas, Octavio
    Pradenas, Lorena
    TECNOLOGIA Y CIENCIAS DEL AGUA, 2018, 9 (03) : 198 - 212
  • [48] The Method of Multi-criteria Parametric Optimization
    Korobiichuk, Igor
    Drevetsky, Volodymyr
    Kuzmych, Lyudmyla
    Kovela, Ivan
    AUTOMATION 2020: TOWARDS INDUSTRY OF THE FUTURE, 2020, 1140 : 87 - 97
  • [49] Multi-Criteria Optimization of a Hexapod Machine
    Lars KÜbler
    Christoph Henninger
    Peter Eberhard
    Multibody System Dynamics, 2005, 14 : 225 - 250
  • [50] Generic constraints handling techniques in constrained multi-criteria optimization and its application
    Liu, Linzhong
    Mu, Haibo
    Yang, Juhua
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2015, 244 (02) : 576 - 591