Pub Date : 2022-08-15DOI: 10.31181/oresta060722090g
H. Gündoğdu, A. Aytekin
{"title":"The Effects of Sustainable Governance to Sustainable Development","authors":"H. Gündoğdu, A. Aytekin","doi":"10.31181/oresta060722090g","DOIUrl":"https://doi.org/10.31181/oresta060722090g","url":null,"abstract":"","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47904628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-20DOI: 10.31181/oresta190222076h
Hendi Herlambang, Zulfa Fitri Ikatrinasari, K. Kosasih
Increasing the speed of the product change-over process is critical by implementing the Single Minute Exchange of Dies (SMED) effectively. The smallest activity variation between operators, activity speed, and process accuracy are identified research targets. This research was developed in the electronic component industry, where the Define-Measure-Analyze-Improve-Control (DMAIC) and Hierarchy Task Analysis (HTA) methods can describe the most crucial and key activities. Therefore, it takes accuracy and reliability between operators to carry out this activity. This paper presents the acceleration of the product change-over process by developing an automated non-contact inspection method in the assembly area using a vision system. The results of the study illustrate that the change-over process can be carried out in single-digit minutes (7 minutes), or reduced by 81%, and the speed of change-over activities between operators is the same.
{"title":"Single-Digit time: Toward a Quick Change-over Process with The SMED method using The Vision System","authors":"Hendi Herlambang, Zulfa Fitri Ikatrinasari, K. Kosasih","doi":"10.31181/oresta190222076h","DOIUrl":"https://doi.org/10.31181/oresta190222076h","url":null,"abstract":"Increasing the speed of the product change-over process is critical by implementing the Single Minute Exchange of Dies (SMED) effectively. The smallest activity variation between operators, activity speed, and process accuracy are identified research targets. This research was developed in the electronic component industry, where the Define-Measure-Analyze-Improve-Control (DMAIC) and Hierarchy Task Analysis (HTA) methods can describe the most crucial and key activities. Therefore, it takes accuracy and reliability between operators to carry out this activity. This paper presents the acceleration of the product change-over process by developing an automated non-contact inspection method in the assembly area using a vision system. The results of the study illustrate that the change-over process can be carried out in single-digit minutes (7 minutes), or reduced by 81%, and the speed of change-over activities between operators is the same.","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44763393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-20DOI: 10.31181/oresta190222046c
Ritwika Chattopadhyay, P. P. Das, S. Chakraborty
In the context of supply chain management, supplier selection can be defined as the process by which organizations score and evaluate a range of alternative suppliers to choose the best possible one who can provide superior quality of raw materials at cheaper rate and lesser lead time. It is a decision making process with multiple trade-offs between various conflicting criteria which in turn helps the organizations identify the suitable suppliers that would establish a robust supply chain assisting in maintaining a competitive edge. The main objective of supplier selection is thus focused on reducing purchase risk, maximizing overall value to the organization, and developing closeness and long-term relationships between the suppliers and the organization. In this paper, while selecting the most suitable supplier for gearboxes in an Indian iron and steel industry, assessments of three decision makers on the performance of five candidate suppliers with respect to five evaluation criteria are first aggregated using rough numbers. The definitive distances of those rough numbers are then treated as the inputs to a 25 full-factorial design plan with the corresponding multi-attributive border approximation area comparison (MABAC) scores as the output variables. Finally, a design of experiments (DoE)-based metamodel is formulated to interlink the computed MABAC scores with the considered criteria. The competing suppliers are ranked based on this rough-MABAC-DoE-based metamodel, which also easies out the computational steps when new suppliers are included in the decision making process.
{"title":"Development of a Rough-MABAC-DoE-based Metamodel for Supplier Selection in an Iron and Steel Industry","authors":"Ritwika Chattopadhyay, P. P. Das, S. Chakraborty","doi":"10.31181/oresta190222046c","DOIUrl":"https://doi.org/10.31181/oresta190222046c","url":null,"abstract":"In the context of supply chain management, supplier selection can be defined as the process by which organizations score and evaluate a range of alternative suppliers to choose the best possible one who can provide superior quality of raw materials at cheaper rate and lesser lead time. It is a decision making process with multiple trade-offs between various conflicting criteria which in turn helps the organizations identify the suitable suppliers that would establish a robust supply chain assisting in maintaining a competitive edge. The main objective of supplier selection is thus focused on reducing purchase risk, maximizing overall value to the organization, and developing closeness and long-term relationships between the suppliers and the organization. In this paper, while selecting the most suitable supplier for gearboxes in an Indian iron and steel industry, assessments of three decision makers on the performance of five candidate suppliers with respect to five evaluation criteria are first aggregated using rough numbers. The definitive distances of those rough numbers are then treated as the inputs to a 25 full-factorial design plan with the corresponding multi-attributive border approximation area comparison (MABAC) scores as the output variables. Finally, a design of experiments (DoE)-based metamodel is formulated to interlink the computed MABAC scores with the considered criteria. The competing suppliers are ranked based on this rough-MABAC-DoE-based metamodel, which also easies out the computational steps when new suppliers are included in the decision making process.","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46480904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-20DOI: 10.31181/oresta040422196m
Saima Mustafa, Arfa Amjad Bajwa, Shafqat Iqbal
Decision making process in stock trading is a complex one. Stock market is a key factor of monetary markets and signs of economic growth. In some circumstances, traditional forecasting methods cannot contract with determining and sometimes data consist of uncertain and imprecise properties which are not handled by quantitative models. In order to achieve the main objective, accuracy and efficiency of time series forecasting, we move towards the fuzzy time series modeling. Fuzzy time series is different from other time series as it is represented in linguistics values rather than a numeric value. The Fuzzy set theory includes many types of membership functions. In this study, we will utilize the Fuzzy approach and trapezoidal membership function to develop the fuzzy generalized auto regression conditional heteroscedasticity (FGARCH) model by using the fuzzy least square techniques to forecasting stock exchange market prices. The experimental results show that the proposed forecasting system can accurately forecast stock prices. The accuracy measures RMSE, MAD, MAPE, MSE, and Theil-U-Statistics have values of 18.17, 15.65, 2.339, 301.998, and 0.003212, respectively, which confirmed that the proposed system is considered to be useful for forecasting the stock index prices, which outperforms conventional GARCH models.
{"title":"A New Fuzzy Grach Model to forecast Stock Market Technical Analysis","authors":"Saima Mustafa, Arfa Amjad Bajwa, Shafqat Iqbal","doi":"10.31181/oresta040422196m","DOIUrl":"https://doi.org/10.31181/oresta040422196m","url":null,"abstract":"Decision making process in stock trading is a complex one. Stock market is a key factor of monetary markets and signs of economic growth. In some circumstances, traditional forecasting methods cannot contract with determining and sometimes data consist of uncertain and imprecise properties which are not handled by quantitative models. In order to achieve the main objective, accuracy and efficiency of time series forecasting, we move towards the fuzzy time series modeling. Fuzzy time series is different from other time series as it is represented in linguistics values rather than a numeric value. The Fuzzy set theory includes many types of membership functions. In this study, we will utilize the Fuzzy approach and trapezoidal membership function to develop the fuzzy generalized auto regression conditional heteroscedasticity (FGARCH) model by using the fuzzy least square techniques to forecasting stock exchange market prices. The experimental results show that the proposed forecasting system can accurately forecast stock prices. The accuracy measures RMSE, MAD, MAPE, MSE, and Theil-U-Statistics have values of 18.17, 15.65, 2.339, 301.998, and 0.003212, respectively, which confirmed that the proposed system is considered to be useful for forecasting the stock index prices, which outperforms conventional GARCH models.","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46246114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-20DOI: 10.31181/oresta240322121n
A. Nicał, K. Sikora
In recent years, changes in demographic structure have been observed worldwide. To sustain the growing population of elderly people with special needs, homes need a radical rethink both in designing new houses and in retrofitting new solutions to existing houses. Designs that facilitate aging in place, designs that maintain thermal comfort, and designs that have net-zero energy demands and low to zero to negative carbon footprints are needed. The article discusses the issues of construction for the elderly. The trends in the demographic development of society in selected countries are presented. Additionally, information on the housing stock for elderly people in Poland is provided. The carbon dioxide emission limits to mitigate climate change make it necessary to find an alternative to concrete and steel, traditional construction materials. In this context, Cross Laminated Timber (CLT) fulfills the sustainability requirements. However, to select the suitable panel a detailed analysis of timber characteristics is required. It is necessary to evaluate mechanical properties in bending, tension, compression, and shear. Since the mechanical properties of certain types of wood differ, their proper selection is challenging. The multi-criteria analysis could address this. In this article, four wood species, spruce, oak, ash, and beech, were evaluated using the Analytic Hierarchy Process (AHP) analysis. Based on the type of construction elements and their functions, analyses were using six mechanical properties as criteria. The optimal type of wood was indicated.
{"title":"Application of Wooden Modular Construction for the Needs of the Elderly","authors":"A. Nicał, K. Sikora","doi":"10.31181/oresta240322121n","DOIUrl":"https://doi.org/10.31181/oresta240322121n","url":null,"abstract":"In recent years, changes in demographic structure have been observed worldwide. To sustain the growing population of elderly people with special needs, homes need a radical rethink both in designing new houses and in retrofitting new solutions to existing houses. Designs that facilitate aging in place, designs that maintain thermal comfort, and designs that have net-zero energy demands and low to zero to negative carbon footprints are needed. The article discusses the issues of construction for the elderly. The trends in the demographic development of society in selected countries are presented. Additionally, information on the housing stock for elderly people in Poland is provided. The carbon dioxide emission limits to mitigate climate change make it necessary to find an alternative to concrete and steel, traditional construction materials. In this context, Cross Laminated Timber (CLT) fulfills the sustainability requirements. However, to select the suitable panel a detailed analysis of timber characteristics is required. It is necessary to evaluate mechanical properties in bending, tension, compression, and shear. Since the mechanical properties of certain types of wood differ, their proper selection is challenging. The multi-criteria analysis could address this. In this article, four wood species, spruce, oak, ash, and beech, were evaluated using the Analytic Hierarchy Process (AHP) analysis. Based on the type of construction elements and their functions, analyses were using six mechanical properties as criteria. The optimal type of wood was indicated.","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45523331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-20DOI: 10.31181/oresta180222016p
Domingo Pavolo, D. Chikobvu
Multiple response surface methodology (MRSM) has been the favorite method for optimizing multiple response processes though it has two weaknesses which challenge the credibility of its solutions. The first weakness is the use of experimentally generated small sample size datasets, and the second is the selection, using classical model selection criteria, of single best models for each response for use in simultaneous optimization to obtain the optimum or desired solution. Classical model selection criteria do not always agree on the best model resulting in model uncertainty. The selection of single best models for each response for simultaneous optimization loses information in rejected models. This work proposes the use of multiple simultaneous optimizations to estimate multiple solutions that are ensembled in solving a conveyor belting cure time problem. The solution is compared with one obtained by simultaneous optimization of single best models for each response. The two results were different. However, results show that it is possible to obtain a more credible solution through ensembling of solutions from multiple simultaneous optimizations.
{"title":"Estimating Rubber Covered Conveyor Belting Cure Times Using Multiple Simultaneous Optimizations Ensemble","authors":"Domingo Pavolo, D. Chikobvu","doi":"10.31181/oresta180222016p","DOIUrl":"https://doi.org/10.31181/oresta180222016p","url":null,"abstract":"Multiple response surface methodology (MRSM) has been the favorite method for optimizing multiple response processes though it has two weaknesses which challenge the credibility of its solutions. The first weakness is the use of experimentally generated small sample size datasets, and the second is the selection, using classical model selection criteria, of single best models for each response for use in simultaneous optimization to obtain the optimum or desired solution. Classical model selection criteria do not always agree on the best model resulting in model uncertainty. The selection of single best models for each response for simultaneous optimization loses information in rejected models. This work proposes the use of multiple simultaneous optimizations to estimate multiple solutions that are ensembled in solving a conveyor belting cure time problem. The solution is compared with one obtained by simultaneous optimization of single best models for each response. The two results were different. However, results show that it is possible to obtain a more credible solution through ensembling of solutions from multiple simultaneous optimizations.","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47403131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-20DOI: 10.31181/oresta250322166r
D. Rossit, F. Tohmé, Rodrigo Introcaso, Jeanette Rodríguez
Industry 4.0 is leveraging the production capabilities of the industry. The deep digitalization that Industry 4.0 promotes enables to extend control skills to an exhaustive detail in the shop floors. Then, new planning strategies can be designed and implemented. We present mathematical models to represent non-permutation flow shop processes, incorporating Industry 4.0 features and customer-focused attention. Basically, we study the impact of lot streaming on the ensuing optimization problems, since the work-in-process inventory control is considerably enhanced by Industry 4.0 technologies. Thus, is possible to take advantage of subdividing the production lots into smaller sublots, as lot streaming proposes. To test this hypothesis we use a novel approach to non-permutation flow shop problems which requires a lot streaming strategy, incorporating total tardiness as objective function. Our analysis indicates that lot streaming improves results increasingly with the number of machines. We also find that the improvement is less steep with more sublots, increasing the computational cost of solutions. This indicates that it is highly relevant to fine tune the maximum number of sublots to avoid extra costs.
{"title":"Mathematical Modelling of Non-Permutation Flow Shop Processes with Lot Streaming in the Smart Manufacturing Era","authors":"D. Rossit, F. Tohmé, Rodrigo Introcaso, Jeanette Rodríguez","doi":"10.31181/oresta250322166r","DOIUrl":"https://doi.org/10.31181/oresta250322166r","url":null,"abstract":"Industry 4.0 is leveraging the production capabilities of the industry. The deep digitalization that Industry 4.0 promotes enables to extend control skills to an exhaustive detail in the shop floors. Then, new planning strategies can be designed and implemented. We present mathematical models to represent non-permutation flow shop processes, incorporating Industry 4.0 features and customer-focused attention. Basically, we study the impact of lot streaming on the ensuing optimization problems, since the work-in-process inventory control is considerably enhanced by Industry 4.0 technologies. Thus, is possible to take advantage of subdividing the production lots into smaller sublots, as lot streaming proposes. To test this hypothesis we use a novel approach to non-permutation flow shop problems which requires a lot streaming strategy, incorporating total tardiness as objective function. Our analysis indicates that lot streaming improves results increasingly with the number of machines. We also find that the improvement is less steep with more sublots, increasing the computational cost of solutions. This indicates that it is highly relevant to fine tune the maximum number of sublots to avoid extra costs.","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47853931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-20DOI: 10.31181/oresta290122001e
Mohamed A. Elkhouli
This study aimed to apply the measurement of the impact of determinants of the change management process (CMP) on the competitive performance (CP) of the employees at the government sector in a practical environment by comparison between the employees’ expectation at the Government of Ras Al-Khaimah compared to the expectation of employees at Ajman Government. Thus, the Emirate of Ajman within the UAE was selected to apply the same scale of measuring which has same conditions of the work of the government sector and similar geographical aspects like the Emirate of RAK. The results have shown a significant impact of the role of direct determinants which were assumed by the current study in the influence of improving the competitiveness of the employees during the implementation to any change management process planned at the level of government sectors. There were five key determinants respectively in terms of impact strength, and those determinants were creation and innovation, institutional values, quality and excellence systems, administrative and legal aspects and finally, the role of leadership.
{"title":"The Demographic and institutional Determinants affecting Manpower’s development at the government sector","authors":"Mohamed A. Elkhouli","doi":"10.31181/oresta290122001e","DOIUrl":"https://doi.org/10.31181/oresta290122001e","url":null,"abstract":"This study aimed to apply the measurement of the impact of determinants of the change management process (CMP) on the competitive performance (CP) of the employees at the government sector in a practical environment by comparison between the employees’ expectation at the Government of Ras Al-Khaimah compared to the expectation of employees at Ajman Government. Thus, the Emirate of Ajman within the UAE was selected to apply the same scale of measuring which has same conditions of the work of the government sector and similar geographical aspects like the Emirate of RAK. The results have shown a significant impact of the role of direct determinants which were assumed by the current study in the influence of improving the competitiveness of the employees during the implementation to any change management process planned at the level of government sectors. There were five key determinants respectively in terms of impact strength, and those determinants were creation and innovation, institutional values, quality and excellence systems, administrative and legal aspects and finally, the role of leadership.","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46473198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-20DOI: 10.31181/oresta190222061s
H. Sharma, Aarti Singh, Dixy Yadav, S. Kar
Accommodation is one of the necessities of tourists and travel agencies' significant responsibilities. With the growing competition and profit-making various tour organising companies have started providing attractive accommodation options to the travellers to win their choices. Present research performs a case study on accommodation providing hotels through designing a strategy to enhance their profit earrings by welcoming more and more tourists. The methodology comprises rough set theory (RST) using the Dominance Based rough set theory (DRST) on the collected data of selected variables such as location, facility, value for money, etc., of hotels. Correspondingly, if and then decision rule has been used to classify these variables. The statistical methods regression analysis has also been used to define each variable's relationship and influence on concerned authorities' decision-making. The results show that hotels and tourists can benefit from the proposed strategy and help in decision making by understanding tourist behaviour, increasing profit, improving services, and quality of hotels.
住宿是游客的必需品之一，也是旅行社的重要职责。随着竞争的加剧和盈利的增加，各种旅行社开始为游客提供有吸引力的住宿选择，以赢得他们的选择。本研究对提供住宿的酒店进行了案例研究，通过设计一种策略来提高其利润，以迎接越来越多的游客。该方法包括基于优势的粗糙集理论（DRST）的粗糙集论（RST），该理论基于所收集的选定变量的数据，如酒店的位置、设施、性价比等。相应地，if and then决策规则被用于对这些变量进行分类。统计方法回归分析也被用来定义每个变量的关系和对有关当局决策的影响。结果表明，酒店和游客可以从所提出的策略中受益，并通过了解游客行为、增加利润、改善服务和酒店质量来帮助决策。
{"title":"Criteria selection and decision making of hotels using Dominance Based Rough Set Theory","authors":"H. Sharma, Aarti Singh, Dixy Yadav, S. Kar","doi":"10.31181/oresta190222061s","DOIUrl":"https://doi.org/10.31181/oresta190222061s","url":null,"abstract":"Accommodation is one of the necessities of tourists and travel agencies' significant responsibilities. With the growing competition and profit-making various tour organising companies have started providing attractive accommodation options to the travellers to win their choices. Present research performs a case study on accommodation providing hotels through designing a strategy to enhance their profit earrings by welcoming more and more tourists. The methodology comprises rough set theory (RST) using the Dominance Based rough set theory (DRST) on the collected data of selected variables such as location, facility, value for money, etc., of hotels. Correspondingly, if and then decision rule has been used to classify these variables. The statistical methods regression analysis has also been used to define each variable's relationship and influence on concerned authorities' decision-making. The results show that hotels and tourists can benefit from the proposed strategy and help in decision making by understanding tourist behaviour, increasing profit, improving services, and quality of hotels.","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47692001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-20DOI: 10.31181/oresta240322136m
D. Mladenović, S. Janković, S. Zdravković, Snezana Mladenovic, Ana Uzelac
The aim of this research is to predict the total and average monthly night traffic on state roads in Serbia, using the technique of supervised machine learning. A set of data on total and average monthly night traffic has been used for training and testing of predictive models. The data set was obtained by counting the traffic on the roads in Serbia, in the period from 2011 to 2020. Various classification and regression prediction models have been tested using the Weka software tool on the available data set and the models based on the K-Nearest Neighbors algorithm, as well as models based on regression trees, have shown the best results. Furthermore, the best model has been chosen by comparing the performances of models. According to all the mentioned criteria, the model based on the K-Nearest Neighbors algorithm has shown the best results. Using this model, the prediction of the total and average nightly traffic per month for the following year at the selected traffic counting locations has been made.
{"title":"Night Traffic Flow Prediction Using K-Nearest Neighbors Algorithm","authors":"D. Mladenović, S. Janković, S. Zdravković, Snezana Mladenovic, Ana Uzelac","doi":"10.31181/oresta240322136m","DOIUrl":"https://doi.org/10.31181/oresta240322136m","url":null,"abstract":"The aim of this research is to predict the total and average monthly night traffic on state roads in Serbia, using the technique of supervised machine learning. A set of data on total and average monthly night traffic has been used for training and testing of predictive models. The data set was obtained by counting the traffic on the roads in Serbia, in the period from 2011 to 2020. Various classification and regression prediction models have been tested using the Weka software tool on the available data set and the models based on the K-Nearest Neighbors algorithm, as well as models based on regression trees, have shown the best results. Furthermore, the best model has been chosen by comparing the performances of models. According to all the mentioned criteria, the model based on the K-Nearest Neighbors algorithm has shown the best results. Using this model, the prediction of the total and average nightly traffic per month for the following year at the selected traffic counting locations has been made.","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47544765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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