Genetic Algorithm as Automated Valuation Model Component in Real Estate Investment Decisions System
Every real-estate related investment decision making process calls for the careful analysis of available information even though it is often carried out in conditions of uncertainty. The paper attempts to minimize the impact of the factor on the quality of real estate investment decisions through th...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2020-12-01
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| Series: | Real Estate Management and Valuation |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/remav-2020-0027 |
| _version_ | 1818609443653287936 |
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| author | Chmielewska Aneta Adamiczka Jerzy Romanowski Michał |
| author_facet | Chmielewska Aneta Adamiczka Jerzy Romanowski Michał |
| author_sort | Chmielewska Aneta |
| collection | DOAJ |
| description | Every real-estate related investment decision making process calls for the careful analysis of available information even though it is often carried out in conditions of uncertainty. The paper attempts to minimize the impact of the factor on the quality of real estate investment decisions through the proposal of application of tools based on the simulation of the process of natural selection and biological evolution. The aim of the study is to analyze the potential of methodology based on genetic algorithms (GA) to build automated valuation models (AVM) in uncertainty conditions and support investment decisions on the real estate market. The developed model facilitates the selection of properties adequate to the adopted assumptions, i.e. individuals best suited to the environment. The tool can be used by real estate investment advisors and potential investors on the market to predict future processes and the proper confrontation of past events with planned events. Even though genetic algorithms are tools that have already found particular application on real estate market, there are still areas that need further studies in the case of more effective uses. The obtained results allow for the possibilities and barriers of applying GA to real estate market analyses to be defined. |
| first_indexed | 2024-12-16T14:58:37Z |
| format | Article |
| id | doaj.art-6fb6a740b0f341788b3b2726b9b4f92d |
| institution | Directory Open Access Journal |
| issn | 2300-5289 |
| language | English |
| last_indexed | 2024-12-16T14:58:37Z |
| publishDate | 2020-12-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Real Estate Management and Valuation |
| spelling | doaj.art-6fb6a740b0f341788b3b2726b9b4f92d2022-12-21T22:27:20ZengSciendoReal Estate Management and Valuation2300-52892020-12-0128411410.1515/remav-2020-0027remav-2020-0027Genetic Algorithm as Automated Valuation Model Component in Real Estate Investment Decisions SystemChmielewska Aneta0Adamiczka Jerzy1Romanowski Michał2Institute of Spatial Economy and Geography, University of Warmia and Mazury in Olsztyn, Olsztyn, PolandAdamiczka ConsultingIndependent researcherEvery real-estate related investment decision making process calls for the careful analysis of available information even though it is often carried out in conditions of uncertainty. The paper attempts to minimize the impact of the factor on the quality of real estate investment decisions through the proposal of application of tools based on the simulation of the process of natural selection and biological evolution. The aim of the study is to analyze the potential of methodology based on genetic algorithms (GA) to build automated valuation models (AVM) in uncertainty conditions and support investment decisions on the real estate market. The developed model facilitates the selection of properties adequate to the adopted assumptions, i.e. individuals best suited to the environment. The tool can be used by real estate investment advisors and potential investors on the market to predict future processes and the proper confrontation of past events with planned events. Even though genetic algorithms are tools that have already found particular application on real estate market, there are still areas that need further studies in the case of more effective uses. The obtained results allow for the possibilities and barriers of applying GA to real estate market analyses to be defined.https://doi.org/10.1515/remav-2020-0027genetic algorithm (ga)uncertaintydecision support systemautomated valuation model (avm)real estate marketc00c10d81r30 |
| spellingShingle | Chmielewska Aneta Adamiczka Jerzy Romanowski Michał Genetic Algorithm as Automated Valuation Model Component in Real Estate Investment Decisions System Real Estate Management and Valuation genetic algorithm (ga) uncertainty decision support system automated valuation model (avm) real estate market c00 c10 d81 r30 |
| title | Genetic Algorithm as Automated Valuation Model Component in Real Estate Investment Decisions System |
| title_full | Genetic Algorithm as Automated Valuation Model Component in Real Estate Investment Decisions System |
| title_fullStr | Genetic Algorithm as Automated Valuation Model Component in Real Estate Investment Decisions System |
| title_full_unstemmed | Genetic Algorithm as Automated Valuation Model Component in Real Estate Investment Decisions System |
| title_short | Genetic Algorithm as Automated Valuation Model Component in Real Estate Investment Decisions System |
| title_sort | genetic algorithm as automated valuation model component in real estate investment decisions system |
| topic | genetic algorithm (ga) uncertainty decision support system automated valuation model (avm) real estate market c00 c10 d81 r30 |
| url | https://doi.org/10.1515/remav-2020-0027 |
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