Pub Date : 2021-09-24DOI: 10.31181/oresta20402059t
Shesagiri Taminana, Lalitha Bhaskari, Arwa A. Mashat, D. Pamučar, Haritha Akkineni
With the Present days increasing demand for the higher performance with the application developers have started considering cloud computing and cloud-based data centres as one of the prime options for hosting the application. Number of parallel research outcomes have for making a data centre secure, the data centre infrastructure must go through the auditing process. During the auditing process, auditors can access VMs, applications and data deployed on the virtual machines. The downside of the data in the VMs can be highly sensitive and during the process of audits, it is highly complex to permits based on the requests and can increase the total time taken to complete the tasks. Henceforth, the demand for the selective and adaptive auditing is the need of the current research. However, these outcomes are criticised for higher time complexity and less accuracy. Thus, this work proposes a predictive method for analysing the characteristics of the VM applications and the characteristics from the auditors and finally granting the access to the virtual machine by building a predictive regression model. The proposed algorithm demonstrates 50% of less time complexity to the other parallel research for making the cloud-based application development industry a safer and faster place.
{"title":"Secure Cloud Auditability for Virtual Machines by Adaptive Characterization Using Machine Learning Methods","authors":"Shesagiri Taminana, Lalitha Bhaskari, Arwa A. Mashat, D. Pamučar, Haritha Akkineni","doi":"10.31181/oresta20402059t","DOIUrl":"https://doi.org/10.31181/oresta20402059t","url":null,"abstract":"With the Present days increasing demand for the higher performance with the application developers have started considering cloud computing and cloud-based data centres as one of the prime options for hosting the application. Number of parallel research outcomes have for making a data centre secure, the data centre infrastructure must go through the auditing process. During the auditing process, auditors can access VMs, applications and data deployed on the virtual machines. The downside of the data in the VMs can be highly sensitive and during the process of audits, it is highly complex to permits based on the requests and can increase the total time taken to complete the tasks. Henceforth, the demand for the selective and adaptive auditing is the need of the current research. However, these outcomes are criticised for higher time complexity and less accuracy. Thus, this work proposes a predictive method for analysing the characteristics of the VM applications and the characteristics from the auditors and finally granting the access to the virtual machine by building a predictive regression model. The proposed algorithm demonstrates 50% of less time complexity to the other parallel research for making the cloud-based application development industry a safer and faster place.","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45411311","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 : 2021-08-15DOI: 10.31181/ORESTA20402013B
Mouhamed Bayane Bouraima, Željko Stević, I. Tanackov, Yanjun Qiu, Herzegovina.
In this study, the performance of Sub-Saharan African railways systems (SSA) is assessed by using an integrated Entropy-MARCOS (Measurement Alternatives and Ranking according to COmpromise Solution) - based methodology. In the first phase, the Entropy method is employed to determine the weights of each sub-criterion of the decision model. This process identifies six main criteria, i.e., safety, security, internal business aspect, intermodal aspect, innovation, and learning aspect, and customer satisfaction which are further supplemented by 13 sub-criteria. In the second phase, the MARCOS method is used to rank the countries based on their railway performance assessment. Based on the results from the proposed method, a sensitivity analysis was carried out through a comparative analysis with seven other multi-criteria decision-making (MCDM) methods. The results of the study indicate that the most weighted sub-criterion is the labor productivity (internal business perspective criteria) followed by the terrorist incidence (security criteria) and the number of employees going through training/exposure sessions (innovation and learning perspective criteria). Moreover, it was revealed that Kenya is the best alternative in terms of its railway performance followed by Ethiopia, Cameroon, Nigeria, and Ghana. Based on the findings from this study, decision-makers can be assisted during the operative, designing, and planning investigations of the railway system through the consideration of these parameters as insert indicators. Also, the findings can help as a benchmark for the performance analysis of other railway systems in other African countries.
{"title":"Assessing the performance of Sub-Saharan African (SSA) railways based on an integrated Entropy-MARCOS approach","authors":"Mouhamed Bayane Bouraima, Željko Stević, I. Tanackov, Yanjun Qiu, Herzegovina.","doi":"10.31181/ORESTA20402013B","DOIUrl":"https://doi.org/10.31181/ORESTA20402013B","url":null,"abstract":"In this study, the performance of Sub-Saharan African railways systems (SSA) is assessed by using an integrated Entropy-MARCOS (Measurement Alternatives and Ranking according to COmpromise Solution) - based methodology. In the first phase, the Entropy method is employed to determine the weights of each sub-criterion of the decision model. This process identifies six main criteria, i.e., safety, security, internal business aspect, intermodal aspect, innovation, and learning aspect, and customer satisfaction which are further supplemented by 13 sub-criteria. In the second phase, the MARCOS method is used to rank the countries based on their railway performance assessment. Based on the results from the proposed method, a sensitivity analysis was carried out through a comparative analysis with seven other multi-criteria decision-making (MCDM) methods. The results of the study indicate that the most weighted sub-criterion is the labor productivity (internal business perspective criteria) followed by the terrorist incidence (security criteria) and the number of employees going through training/exposure sessions (innovation and learning perspective criteria). Moreover, it was revealed that Kenya is the best alternative in terms of its railway performance followed by Ethiopia, Cameroon, Nigeria, and Ghana. Based on the findings from this study, decision-makers can be assisted during the operative, designing, and planning investigations of the railway system through the consideration of these parameters as insert indicators. Also, the findings can help as a benchmark for the performance analysis of other railway systems in other African countries.","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42584206","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 : 2021-08-15DOI: 10.31181/ORESTA20402001K
Navid Kazemitash, H. Fazlollahtabar, M. Abbaspour
This paper concerns with the integration of rough set theory with the Best Worst method to evaluate information system performance within supplier selection problem of biofuel companies. First, a set of main criteria and sub-criteria are collected and then to include uncertainty in decision making, rough set theory is employed. The rough best worst method is applied for weighing and supplier evaluation with respect to information system performance and environmental impacts. Further, a case study is conducted for biofuel company supplier selection and the results imply the effectiveness of the approach in tactical performance evaluation. The best criteria effective on the green supplier selection of ISs performance is determined to be Quality.
{"title":"Rough Best-Worst Method for Supplier Selection in Biofuel Companies based on Green criteria","authors":"Navid Kazemitash, H. Fazlollahtabar, M. Abbaspour","doi":"10.31181/ORESTA20402001K","DOIUrl":"https://doi.org/10.31181/ORESTA20402001K","url":null,"abstract":"This paper concerns with the integration of rough set theory with the Best Worst method to evaluate information system performance within supplier selection problem of biofuel companies. First, a set of main criteria and sub-criteria are collected and then to include uncertainty in decision making, rough set theory is employed. The rough best worst method is applied for weighing and supplier evaluation with respect to information system performance and environmental impacts. Further, a case study is conducted for biofuel company supplier selection and the results imply the effectiveness of the approach in tactical performance evaluation. The best criteria effective on the green supplier selection of ISs performance is determined to be Quality.","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49462768","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 : 2021-06-15DOI: 10.31181/oresta20402036f
Dimas Mukhlis Hidayat Fathurohman, H. Purba, A. Trimarjoko
Automotive service industry currently holds an important role in helping to increase customer satisfaction. Various strategies are carried out to win the competition for increasing customer satisfaction. Quality service combined with the right instruments can be used to increase customer satisfaction and loyalty. Customer satisfaction is the key to success in the manufacturing and service industries. Service quality is an important attribute and it is a key factor in service industries. Improving lead time service in automotive Toyota dealer service industries is the focus of this research. Value Stream Mapping succeeded in identifying problems that were happening as an impact of waiting for services, washing processes, and length of service processes. The DMAIC (Define, Measure, Analyze, Improve and Control) method assisted by tools of quality successfully analyzed and gave recommended corrective actions to reduce the lead time of Express Maintenance Service from 120.06 minutes to 64.00 minutes or improved 53% per service cycle, and succeeded in increasing the capability of the service process from 1.96 sigma to 3.80 sigma. Quality of service can be improved to get customer satisfaction, increase company profitability, and increase the competitiveness of companies in maintaining the sustainability of the industry in the future.
{"title":"Value Stream Mapping and Six Sigma Methods to Improve Service Quality at Automotive Services in indonesia","authors":"Dimas Mukhlis Hidayat Fathurohman, H. Purba, A. Trimarjoko","doi":"10.31181/oresta20402036f","DOIUrl":"https://doi.org/10.31181/oresta20402036f","url":null,"abstract":"Automotive service industry currently holds an important role in helping to increase customer satisfaction. Various strategies are carried out to win the competition for increasing customer satisfaction. Quality service combined with the right instruments can be used to increase customer satisfaction and loyalty. Customer satisfaction is the key to success in the manufacturing and service industries. Service quality is an important attribute and it is a key factor in service industries. Improving lead time service in automotive Toyota dealer service industries is the focus of this research. Value Stream Mapping succeeded in identifying problems that were happening as an impact of waiting for services, washing processes, and length of service processes. The DMAIC (Define, Measure, Analyze, Improve and Control) method assisted by tools of quality successfully analyzed and gave recommended corrective actions to reduce the lead time of Express Maintenance Service from 120.06 minutes to 64.00 minutes or improved 53% per service cycle, and succeeded in increasing the capability of the service process from 1.96 sigma to 3.80 sigma. Quality of service can be improved to get customer satisfaction, increase company profitability, and increase the competitiveness of companies in maintaining the sustainability of the industry in the future.","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41260132","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 : 2021-06-15DOI: 10.31181/oresta20402079n
Gopal M. Naik, R. Kishore, Seyed Ali Mousavi Dehmourdi
Contractor prequalification assessment in the construction industry is an essential part of the project development process because contractors play a pivotal role in the extension of projects and resources. The main objective of the present study is comprised prequalification assessment for classifying contractors by applied the EDAS method for recognizing the contractors' potential before competitive tendering and obtaining bids. First, an inclusive, detailed list of 56 sub-factors under 5 main factors for project prequalification was compiled following a thorough literature review, and review of contractors by experts of Bandar Imam Khomeini municipality who already have done projects with contractors. Second, used the CRITIC method for obtained the weighing and importance of each factor. Third, classified the contractors by applied the EDAS system for recognizing the contractors' potential before competitive tendering and obtaining bids. Finally, the prequalification assessment process was developed to obtaining the rank of each contractor and help the stakeholders to select the right contractors. The effectiveness of the present approach was tested by applying it to a case study of the prequalification assessment of four construction companies' in Bandar Imam Khomeini municipality, Khuzestan, Iran. It is worth mentioning that the prequalification assessment by the proposed approach is approved by the project stakeholders and is consistent with their expectations. It can be concluded that based on relevant ranking and weighing of companies that procedure can be extended to the same studies in this regard, and the contribution of the present study is to propose a support system for prequalification and identification of contractors' ability, before assigning projects to companies for success in projects.
{"title":"Modeling a Multi-Criteria Decision Support System for Prequalification Assessment of Construction Contractors using CRITIC and EDAS Models","authors":"Gopal M. Naik, R. Kishore, Seyed Ali Mousavi Dehmourdi","doi":"10.31181/oresta20402079n","DOIUrl":"https://doi.org/10.31181/oresta20402079n","url":null,"abstract":"Contractor prequalification assessment in the construction industry is an essential part of the project development process because contractors play a pivotal role in the extension of projects and resources. The main objective of the present study is comprised prequalification assessment for classifying contractors by applied the EDAS method for recognizing the contractors' potential before competitive tendering and obtaining bids. First, an inclusive, detailed list of 56 sub-factors under 5 main factors for project prequalification was compiled following a thorough literature review, and review of contractors by experts of Bandar Imam Khomeini municipality who already have done projects with contractors. Second, used the CRITIC method for obtained the weighing and importance of each factor. Third, classified the contractors by applied the EDAS system for recognizing the contractors' potential before competitive tendering and obtaining bids. Finally, the prequalification assessment process was developed to obtaining the rank of each contractor and help the stakeholders to select the right contractors. The effectiveness of the present approach was tested by applying it to a case study of the prequalification assessment of four construction companies' in Bandar Imam Khomeini municipality, Khuzestan, Iran. It is worth mentioning that the prequalification assessment by the proposed approach is approved by the project stakeholders and is consistent with their expectations. It can be concluded that based on relevant ranking and weighing of companies that procedure can be extended to the same studies in this regard, and the contribution of the present study is to propose a support system for prequalification and identification of contractors' ability, before assigning projects to companies for success in projects.","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49455279","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 : 2021-06-15DOI: 10.31181/oresta20402102y
Özlem Yorulmaz, Sultan Kuzu Yıldırım, Bahadır Fatih Yıldırım
In this paper, 81 Turkish provinces with different development levels were ranked using the TOPSIS method. To evaluate the ranking with TOPSIS, we presented an improvement to Mahalanobis distances, by considering a robust MM estimator of the covariance matrix to deal with the presence of outliers in the dataset. Additionally, the homogenous subsets, which were obtained from the robust Mahalanobis distance-based TOPSIS were compared with robust cluster analysis. According to our findings, robust TOPSIS-M scores reflect the inter-class differences in economic developments of provinces spanning from the extremely low to the extremely high level of economic developments. Considering indicators of economic development, which are often used in the literature, İstanbul ranked first, Ankara second, and İzmir third according to the Robust TOPSIS-M method. Moreover, with the Robust Cluster analysis, these provinces were diagnosed as outliers and it was seen that obtained clusters were compatible with the ranking of Robust TOPSIS-M.
{"title":"Robust Mahalanobis Distance based TOPSIS to Evaluate the Economic Development of Provinces","authors":"Özlem Yorulmaz, Sultan Kuzu Yıldırım, Bahadır Fatih Yıldırım","doi":"10.31181/oresta20402102y","DOIUrl":"https://doi.org/10.31181/oresta20402102y","url":null,"abstract":"In this paper, 81 Turkish provinces with different development levels were ranked using the TOPSIS method. To evaluate the ranking with TOPSIS, we presented an improvement to Mahalanobis distances, by considering a robust MM estimator of the covariance matrix to deal with the presence of outliers in the dataset. Additionally, the homogenous subsets, which were obtained from the robust Mahalanobis distance-based TOPSIS were compared with robust cluster analysis. According to our findings, robust TOPSIS-M scores reflect the inter-class differences in economic developments of provinces spanning from the extremely low to the extremely high level of economic developments. Considering indicators of economic development, which are often used in the literature, İstanbul ranked first, Ankara second, and İzmir third according to the Robust TOPSIS-M method. Moreover, with the Robust Cluster analysis, these provinces were diagnosed as outliers and it was seen that obtained clusters were compatible with the ranking of Robust TOPSIS-M.","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44698205","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 : 2021-06-15DOI: 10.31181/oresta20402140z
S. Zolfani, Ali Ebadi Torkayesh, Ramin Bazrafshan
Policy-making is an undeniable decision-making process in every company where different kinds of decisions are taken based on different goals and preferences in each vision. “Prospective Multiple Attribute Decision Making (PMADM)” is one of the well-known decision-making frameworks that have been used as a flexible decision-making tool for developing policies and making future decisions over different periods. This study presents a multi attribute problem with three different visions where a decision-making process is required for each vision in order to prioritize the potential set of alternatives. Evaluation Based on the Distance from the Average Solution (EDAS) is used as a MADM model to show the applicability and feasibility of the PMADM framework. A vision-based weighting system (ViWeS) prepares a new opportunity to take proper decisions in different visions and time requirements. This research is analyzed three-time vision (Current, 2025, and 2030) and showed by changing the time, the rank of the alternatives also is changed. In numerical example is indicated in the current vision, Alternative 5 gets rank one and alternative six get rank 2, for 2025 vision, the rank one and two don’t change, and in vision 2030, the rank of one does not change, but the rank of second change from Alternative 6 to 3.
{"title":"Railway communication system; Reliability; Mean time to failure; Markov process; Sensitivity","authors":"S. Zolfani, Ali Ebadi Torkayesh, Ramin Bazrafshan","doi":"10.31181/oresta20402140z","DOIUrl":"https://doi.org/10.31181/oresta20402140z","url":null,"abstract":"Policy-making is an undeniable decision-making process in every company where different kinds of decisions are taken based on different goals and preferences in each vision. “Prospective Multiple Attribute Decision Making (PMADM)” is one of the well-known decision-making frameworks that have been used as a flexible decision-making tool for developing policies and making future decisions over different periods. This study presents a multi attribute problem with three different visions where a decision-making process is required for each vision in order to prioritize the potential set of alternatives. Evaluation Based on the Distance from the Average Solution (EDAS) is used as a MADM model to show the applicability and feasibility of the PMADM framework. A vision-based weighting system (ViWeS) prepares a new opportunity to take proper decisions in different visions and time requirements. This research is analyzed three-time vision (Current, 2025, and 2030) and showed by changing the time, the rank of the alternatives also is changed. In numerical example is indicated in the current vision, Alternative 5 gets rank one and alternative six get rank 2, for 2025 vision, the rank one and two don’t change, and in vision 2030, the rank of one does not change, but the rank of second change from Alternative 6 to 3.","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43157416","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 : 2021-06-15DOI: 10.31181/oresta20402055a
Talip Arsu, Ejder Ayçin
Exhausted natural resources and deteriorating ecological balance, together with the social privileges that people expect to have, are proof that the development of countries cannot be reduced to economic development alone. In this respect, this study aimed to evaluate the economic, social and environmental aspects of Organization for Economic Co-operation and Development (OECD) countries. Within this scope, the countries were firstly divided into two groups by performing cluster analysis in order to create more homogeneous country groups. Then, 12 criteria, consisting of four economic, four social and four environmental criteria, were determined by considering the literature and expert opinions. The criteria importance through intercriteria correlation (CRITIC) method was used to weight the determined criteria and using the calculated criterion weights, the countries in each cluster were then evaluated with the measurement of alternatives and ranking according to compromise solution (MARCOS) method. As a result, the most successful countries in the first cluster were determined as Switzerland, Denmark and Ireland with 68.8%, 62.7% and 62.5% performance scores, respectively. Whereas, the most unsuccessful countries were USA, Canada and Australia with 49.8%, 50.0% and 50.1% performance scores, respectively. The most successful countries in the second cluster were found as Slovenia, Spain and Portugal with 65.9%, 65.5% and 64.5% performance scores, while the most unsuccessful countries were Turkey, Chile and Colombia with 45.9%, 55.4% and 55.9% performance scores, respectively. Finally, in order to test the sensitivity of the MARCOS method, the solution was repeated with the MAIRCA, WASPAS, MABAC and CoCoSo methods using the weights obtained by the CRITIC method. A high correlation (greater than 80%) was found between the rankings acquired using the other methods and the rankings obtained by the MARCOS method.
{"title":"Evaluation of OECD Countries with Multi-Criteria Decision-Making Methods in terms of Economic, Social and Environmental Aspects","authors":"Talip Arsu, Ejder Ayçin","doi":"10.31181/oresta20402055a","DOIUrl":"https://doi.org/10.31181/oresta20402055a","url":null,"abstract":"Exhausted natural resources and deteriorating ecological balance, together with the social privileges that people expect to have, are proof that the development of countries cannot be reduced to economic development alone. In this respect, this study aimed to evaluate the economic, social and environmental aspects of Organization for Economic Co-operation and Development (OECD) countries. Within this scope, the countries were firstly divided into two groups by performing cluster analysis in order to create more homogeneous country groups. Then, 12 criteria, consisting of four economic, four social and four environmental criteria, were determined by considering the literature and expert opinions. The criteria importance through intercriteria correlation (CRITIC) method was used to weight the determined criteria and using the calculated criterion weights, the countries in each cluster were then evaluated with the measurement of alternatives and ranking according to compromise solution (MARCOS) method. As a result, the most successful countries in the first cluster were determined as Switzerland, Denmark and Ireland with 68.8%, 62.7% and 62.5% performance scores, respectively. Whereas, the most unsuccessful countries were USA, Canada and Australia with 49.8%, 50.0% and 50.1% performance scores, respectively. The most successful countries in the second cluster were found as Slovenia, Spain and Portugal with 65.9%, 65.5% and 64.5% performance scores, while the most unsuccessful countries were Turkey, Chile and Colombia with 45.9%, 55.4% and 55.9% performance scores, respectively. Finally, in order to test the sensitivity of the MARCOS method, the solution was repeated with the MAIRCA, WASPAS, MABAC and CoCoSo methods using the weights obtained by the CRITIC method. A high correlation (greater than 80%) was found between the rankings acquired using the other methods and the rankings obtained by the MARCOS method.","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49407567","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 : 2021-06-15DOI: 10.31181/oresta20402124r
M. Ram, Vaishali Tyagi
In the present study, a railway communication system (RCS) reliability model is developed based on system failure. The proposed RCS has control centre and stations which are arranged in such a manner that failure of control centre or a single station stops the working of overall system i.e., all switches must be working for communication to be available. To improve the reliability of the proposed communication system, a ring architecture is employed. In this architecture one additional communication path is connected in parallel configuration. Provision of two path of communication ensures that failure of one path will not cause a communication failure and communication will be available through additional path. All failures of RCS are exponentially distributed. Mathematical modelling of the system is carried out using Markov process by which the differential equations are generated. These differential equations are further used to evaluate the reliability measures like availability, reliability, mean time to failure of the proposed RCS. Likewise, sensitivity analysis is done to determine the impact of failures on RCS’s performance measures. The proposed Markov process-based model gives the information about the failure and working of the multi- state railway communication system. Finally, numerical results are provided with graphs to demonstrates the usefulness of the findings.
{"title":"RELIABILITY CHARACTERISTICS OF RAILWAY COMMUNICATION SYSTEM SUBJECT TO SWITCH FAILURE","authors":"M. Ram, Vaishali Tyagi","doi":"10.31181/oresta20402124r","DOIUrl":"https://doi.org/10.31181/oresta20402124r","url":null,"abstract":"In the present study, a railway communication system (RCS) reliability model is developed based on system failure. The proposed RCS has control centre and stations which are arranged in such a manner that failure of control centre or a single station stops the working of overall system i.e., all switches must be working for communication to be available. To improve the reliability of the proposed communication system, a ring architecture is employed. In this architecture one additional communication path is connected in parallel configuration. Provision of two path of communication ensures that failure of one path will not cause a communication failure and communication will be available through additional path. All failures of RCS are exponentially distributed. Mathematical modelling of the system is carried out using Markov process by which the differential equations are generated. These differential equations are further used to evaluate the reliability measures like availability, reliability, mean time to failure of the proposed RCS. Likewise, sensitivity analysis is done to determine the impact of failures on RCS’s performance measures. The proposed Markov process-based model gives the information about the failure and working of the multi- state railway communication system. Finally, numerical results are provided with graphs to demonstrates the usefulness of the findings.","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43661586","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}
The current research work deals with an identification of different lean strategies and extraction to relevant strategies after discussion with experts and gives the answer of a question “how lean manufacturing strategies can help the organization to enhance the efficiency of the organization with great effectiveness?” In this research work, thirty-six lean strategies have been identified and out of which thirteen lean strategies were filtered in respect of highly importance value by factor analysis using software SPSS 21. Further, to identify and analyze the inter-relationship among filtered strategies, an Interpretive Structural Modeling (ISM) with Fuzzy Matriced’ Impacts Croise´s Multiplication Applique´e a UN Classement (MICMAC) approach has been used. Fuzzy MICMAC help to understand the dependence and driver’s power of the lean strategies. The mutual importance of extracted strategies has been discussed through developing the ISM model and the individual assessment of each strategy with each of the other strategies has been derived using the Fuzzy MICMAC approach.
{"title":"Modeling and Analysis of Lean Manufacturing Strategies Using ISM-Fuzzy MICMAC Approach","authors":"M. Tyagi, Dilbagh Panchal, D. Kumar, R. S. Walia","doi":"10.31181/ORESTA2040123T","DOIUrl":"https://doi.org/10.31181/ORESTA2040123T","url":null,"abstract":"The current research work deals with an identification of different lean strategies and extraction to relevant strategies after discussion with experts and gives the answer of a question “how lean manufacturing strategies can help the organization to enhance the efficiency of the organization with great effectiveness?” In this research work, thirty-six lean strategies have been identified and out of which thirteen lean strategies were filtered in respect of highly importance value by factor analysis using software SPSS 21. Further, to identify and analyze the inter-relationship among filtered strategies, an Interpretive Structural Modeling (ISM) with Fuzzy Matriced’ Impacts Croise´s Multiplication Applique´e a UN Classement (MICMAC) approach has been used. Fuzzy MICMAC help to understand the dependence and driver’s power of the lean strategies. The mutual importance of extracted strategies has been discussed through developing the ISM model and the individual assessment of each strategy with each of the other strategies has been derived using the Fuzzy MICMAC approach.","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42270836","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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