Optimization Methods as a Base for Decision Making in Land Consolidation Projects Ranking

Goran Marinković, Zoran Ilić, Milan Trifković, Jelena Tatalović () and Marko Božić
Additional contact information
Goran Marinković: Faculty of Technical Sciences, University of Novi Sad, 21000 Novi Sad, Serbia
Zoran Ilić: Faculty of Technical Sciences, University of Novi Sad, 21000 Novi Sad, Serbia
Milan Trifković: Faculty of Civil Engineering Subotica, University of Novi Sad, 24000 Subotica, Serbia
Jelena Tatalović: Faculty of Civil Engineering Subotica, University of Novi Sad, 24000 Subotica, Serbia
Marko Božić: Meixner d.o.o., Hermanova 16/G, 10000 Zagreb, Croatia

Land, 2022, vol. 11, issue 9, 1-12

Abstract: 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.

Keywords: integral assessment; risk reducing; rural area; cadastral municipality; standard deviation; null hypothesis (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2073-445X/11/9/1466/pdf (application/pdf)
https://www.mdpi.com/2073-445X/11/9/1466/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:11:y:2022:i:9:p:1466-:d:905106

Access Statistics for this article

Land is currently edited by Ms. Carol Ma

More articles in Land from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().