Optimization Methods as a Base for Decision Making in Land Consolidation Projects Ranking
Land consolidation (LC) is an activity that brings numerous benefits to rural areas. However, being resource demanding, the LC requires a decision on where it should be provided or where the limited resources should be distributed in order to maximize its effects. In order to avoid the subjective de...
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Format: | Article |
Language: | English |
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MDPI AG
2022-09-01
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Series: | Land |
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Online Access: | https://www.mdpi.com/2073-445X/11/9/1466 |
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author | Goran Marinković Zoran Ilić Milan Trifković Jelena Tatalović Marko Božić |
author_facet | Goran Marinković Zoran Ilić Milan Trifković Jelena Tatalović Marko Božić |
author_sort | Goran Marinković |
collection | DOAJ |
description | Land consolidation (LC) is an activity that brings numerous benefits to rural areas. However, being resource demanding, the LC requires a decision on where it should be provided or where the limited resources should be distributed in order to maximize its effects. In order to avoid the subjective decision maker’s preferences, optimization methods for identifying the priorities are recommended. Bearing in mind that every optimization method could give different results, we proposed the utilization of multiple optimization methods for ranking the cadastral municipalities which are candidates for providing LC. In this research, the main aim was to find if it is possible to avoid the subjective decision making in cadastral municipalities (CM) as a candidate for LC ranking by utilizing the statistical approach. Additionally, in this research, the analysis was provided, varying the number of optimization criteria. In this research, two assumptions were adopted: (1) every single optimization method has the same weight, and (2) the differences between different ranks are results of random errors. After determining the average ranking of a certain cadastral municipality, its interval of ranking is calculated by using the Student’s distribution. Cadastral municipalities that belong within the interval of available resources are candidates for providing LC. In the case study, fifteen cadastral municipalities were researched, including eight and ten criteria for optimization, and results showed that there are significant differences between ranks of cadastral municipalities varying depending on the method utilized. |
first_indexed | 2024-03-09T23:26:14Z |
format | Article |
id | doaj.art-48674c8eb6a4456098268c0369b03850 |
institution | Directory Open Access Journal |
issn | 2073-445X |
language | English |
last_indexed | 2024-03-09T23:26:14Z |
publishDate | 2022-09-01 |
publisher | MDPI AG |
record_format | Article |
series | Land |
spelling | doaj.art-48674c8eb6a4456098268c0369b038502023-11-23T17:17:31ZengMDPI AGLand2073-445X2022-09-01119146610.3390/land11091466Optimization Methods as a Base for Decision Making in Land Consolidation Projects RankingGoran Marinković0Zoran Ilić1Milan Trifković2Jelena Tatalović3Marko Božić4Faculty of Technical Sciences, University of Novi Sad, 21000 Novi Sad, SerbiaFaculty of Technical Sciences, University of Novi Sad, 21000 Novi Sad, SerbiaFaculty of Civil Engineering Subotica, University of Novi Sad, 24000 Subotica, SerbiaFaculty of Civil Engineering Subotica, University of Novi Sad, 24000 Subotica, SerbiaMeixner d.o.o., Hermanova 16/G, 10000 Zagreb, CroatiaLand consolidation (LC) is an activity that brings numerous benefits to rural areas. However, being resource demanding, the LC requires a decision on where it should be provided or where the limited resources should be distributed in order to maximize its effects. In order to avoid the subjective decision maker’s preferences, optimization methods for identifying the priorities are recommended. Bearing in mind that every optimization method could give different results, we proposed the utilization of multiple optimization methods for ranking the cadastral municipalities which are candidates for providing LC. In this research, the main aim was to find if it is possible to avoid the subjective decision making in cadastral municipalities (CM) as a candidate for LC ranking by utilizing the statistical approach. Additionally, in this research, the analysis was provided, varying the number of optimization criteria. In this research, two assumptions were adopted: (1) every single optimization method has the same weight, and (2) the differences between different ranks are results of random errors. After determining the average ranking of a certain cadastral municipality, its interval of ranking is calculated by using the Student’s distribution. Cadastral municipalities that belong within the interval of available resources are candidates for providing LC. In the case study, fifteen cadastral municipalities were researched, including eight and ten criteria for optimization, and results showed that there are significant differences between ranks of cadastral municipalities varying depending on the method utilized.https://www.mdpi.com/2073-445X/11/9/1466integral assessmentrisk reducingrural areacadastral municipalitystandard deviationnull hypothesis |
spellingShingle | Goran Marinković Zoran Ilić Milan Trifković Jelena Tatalović Marko Božić Optimization Methods as a Base for Decision Making in Land Consolidation Projects Ranking Land integral assessment risk reducing rural area cadastral municipality standard deviation null hypothesis |
title | Optimization Methods as a Base for Decision Making in Land Consolidation Projects Ranking |
title_full | Optimization Methods as a Base for Decision Making in Land Consolidation Projects Ranking |
title_fullStr | Optimization Methods as a Base for Decision Making in Land Consolidation Projects Ranking |
title_full_unstemmed | Optimization Methods as a Base for Decision Making in Land Consolidation Projects Ranking |
title_short | Optimization Methods as a Base for Decision Making in Land Consolidation Projects Ranking |
title_sort | optimization methods as a base for decision making in land consolidation projects ranking |
topic | integral assessment risk reducing rural area cadastral municipality standard deviation null hypothesis |
url | https://www.mdpi.com/2073-445X/11/9/1466 |
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