Comparison of Selected Mathematical Programming Models Used for Sustainable Land and Farm Management

The aim of this study is to compare three mathematical programing models used for sustainable land and farm management. The sample for the comparison was 219 agricultural holdings participating as beneficiaries of the measure ‘Modernization of agricultural holdings’ in the Rural Development Plan at...

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Bibliographic Details
Published in:Land (Basel) 2022-08, Vol.11 (8), p.1293
Main Author: Moulogianni, Christina
Format: Article
Language:English
Subjects:
Agricultural land
Agricultural production
Agriculture
Common Agricultural Policy
Comparative analysis
Decision making
Economic models
Environmental impact
Environmental indicators
Farm management
Farmers
Farms
Goal programming
land management
linear
Linear programming
Literature reviews
Mathematical analysis
Mathematical models
Mathematical programming
Methods
Modernization
multi-criteria
positive
Rural development
Sustainability
Sustainable development
Utility functions
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Summary:The aim of this study is to compare three mathematical programing models used for sustainable land and farm management. The sample for the comparison was 219 agricultural holdings participating as beneficiaries of the measure ‘Modernization of agricultural holdings’ in the Rural Development Plan at the Region of Central Macedonia in Greece. Using the crop plan of the agricultural land of these farms the mathematical programming models calculate the optimum solution under different and conflicting goals. The results of the methodologies of Linear Programming (LP), of Positive Mathematical Programming (PMP) and Weighted Goal Programming (WGP), are compared in terms of the proposed agricultural land changes. The sustainability of farms is measured with the use of eleven economic, social, and environmental indicators. Each model has some unique advantages and disadvantages that can enable it to be implemented in particular situations. In the conclusions to this research the characteristics of each model are highlighted.
ISSN:2073-445X
2073-445X
DOI:10.3390/land11081293