Sultan Almotairi, Olayan Alharbi, Zaid Alzaid, Badr Almutairi, Basma Mohamed
Let G = (V, E) be a connected, basic, and finite graph. A subset of V(G) is said to be a resolving set if for any y ∈ V(G), the code of y with regards to T, represented by
{"title":"The Secure Metric Dimension of the Globe Graph and the Flag Graph","authors":"Sultan Almotairi, Olayan Alharbi, Zaid Alzaid, Badr Almutairi, Basma Mohamed","doi":"10.1155/2024/3084976","DOIUrl":"https://doi.org/10.1155/2024/3084976","url":null,"abstract":"Let <i>G</i> = (<i>V</i>, <i>E</i>) be a connected, basic, and finite graph. A subset <span><svg height=\"12.5794pt\" style=\"vertical-align:-3.29107pt\" version=\"1.1\" viewbox=\"-0.0498162 -9.28833 19.548 12.5794\" width=\"19.548pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,0,0)\"></path></g><g transform=\"matrix(.013,0,0,-0.013,11.917,0)\"></path></g></svg><span></span><svg height=\"12.5794pt\" style=\"vertical-align:-3.29107pt\" version=\"1.1\" viewbox=\"23.1301838 -9.28833 19.35 12.5794\" width=\"19.35pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,23.18,0)\"></path></g><g transform=\"matrix(.013,0,0,-0.013,27.691,0)\"></path></g><g transform=\"matrix(.0091,0,0,-0.0091,34.62,3.132)\"></path></g><g transform=\"matrix(.013,0,0,-0.013,39.566,0)\"></path></g></svg><span></span><svg height=\"12.5794pt\" style=\"vertical-align:-3.29107pt\" version=\"1.1\" viewbox=\"44.6591838 -9.28833 14.84 12.5794\" width=\"14.84pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,44.709,0)\"><use xlink:href=\"#g113-118\"></use></g><g transform=\"matrix(.0091,0,0,-0.0091,51.638,3.132)\"></path></g><g transform=\"matrix(.013,0,0,-0.013,56.585,0)\"><use xlink:href=\"#g113-45\"></use></g></svg><span></span><svg height=\"12.5794pt\" style=\"vertical-align:-3.29107pt\" version=\"1.1\" viewbox=\"61.6781838 -9.28833 18.427 12.5794\" width=\"18.427pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,61.728,0)\"></path></g><g transform=\"matrix(.013,0,0,-0.013,66.871,0)\"><use xlink:href=\"#g113-47\"></use></g><g transform=\"matrix(.013,0,0,-0.013,72.014,0)\"><use xlink:href=\"#g113-47\"></use></g><g transform=\"matrix(.013,0,0,-0.013,77.191,0)\"><use xlink:href=\"#g113-45\"></use></g></svg><span></span><svg height=\"12.5794pt\" style=\"vertical-align:-3.29107pt\" version=\"1.1\" viewbox=\"82.28418380000001 -9.28833 16.887 12.5794\" width=\"16.887pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,82.334,0)\"><use xlink:href=\"#g113-118\"></use></g><g transform=\"matrix(.0091,0,0,-0.0091,89.263,3.132)\"></path></g><g transform=\"matrix(.013,0,0,-0.013,94.41,0)\"></path></g></svg></span> of <i>V</i>(<i>G</i>) is said to be a resolving set if for any <i>y</i> ∈ <i>V</i>(<i>G</i>), the code of <i>y</i> with regards to <i>T</i>, represented by <span><svg height=\"12.7178pt\" style=\"vertical-align:-3.42947pt\" version=\"1.1\" viewbox=\"-0.0498162 -9.28833 31.7255 12.7178\" width=\"31.7255pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,0,0)\"></path></g><g transform=\"matrix(.0091,0,0,-0.0091,8.619,3.132)\"></path></g><g transform=\"matrix(.013,0,0,-0.013,15.009,0)\"></path></g><g transform=\"matrix(.013,0,0,-0.013,19.507,0)\"></path></g><g transform=\"matrix(.013,0,0,-","PeriodicalId":44178,"journal":{"name":"Advances in Operations Research","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140615760","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}
Network Data Envelopment Analysis (NDEA) models assess the processes of the underlying system at a certain moment and disregard the dynamic effects in the production process. Hence, distorted efficiency evaluation is gained that might give misleading information to decision-making units (DMUs). Malmquist–Luenberger Productivity Index (MPI) assesses efficiency changes over time, which are measured as the product of recovery and frontier-shift terms, both coming from the DEA framework. In this study, a form of MPI involving network structure for evaluating DMUs in the presence of uncertainty and undesirable outputs in two periods of time is presented. To cope with uncertainty, we use the stochastic p-robust approach and the weak disposability of Kuosmanen (American Journal Agricultural Economics 87 (4):1077–1082, 2005) proposed to take care of undesirable outputs. The proposed fractional models for stages and overall system are linearized by applying the Charnes and Cooper transformation. Finally, the proposed models are applied to evaluate the efficiency of 11 petroleum wells to identify the main factors determining their productivity, utilizing the data from the 2020 to 2021 period. The results show that the management of resource consumption, especially equipment and capital, is not appropriate and investment is inadequate. Although the depreciation rate of capital facilities in this industry is high, the purpose of the investment is not to upgrade the level of technology.
{"title":"Malmquist–Luenberger Productivity Index for a Two-Stage Structure in the Presence of Undesirable Outputs and Uncertainty","authors":"Rita Shakouri, Maziar Salahi","doi":"10.1155/2024/6905897","DOIUrl":"https://doi.org/10.1155/2024/6905897","url":null,"abstract":"Network Data Envelopment Analysis (NDEA) models assess the processes of the underlying system at a certain moment and disregard the dynamic effects in the production process. Hence, distorted efficiency evaluation is gained that might give misleading information to decision-making units (DMUs). Malmquist–Luenberger Productivity Index (MPI) assesses efficiency changes over time, which are measured as the product of recovery and frontier-shift terms, both coming from the DEA framework. In this study, a form of MPI involving network structure for evaluating DMUs in the presence of uncertainty and undesirable outputs in two periods of time is presented. To cope with uncertainty, we use the stochastic p-robust approach and the weak disposability of Kuosmanen (American Journal Agricultural Economics 87 (4):1077–1082, 2005) proposed to take care of undesirable outputs. The proposed fractional models for stages and overall system are linearized by applying the Charnes and Cooper transformation. Finally, the proposed models are applied to evaluate the efficiency of 11 petroleum wells to identify the main factors determining their productivity, utilizing the data from the 2020 to 2021 period. The results show that the management of resource consumption, especially equipment and capital, is not appropriate and investment is inadequate. Although the depreciation rate of capital facilities in this industry is high, the purpose of the investment is not to upgrade the level of technology.","PeriodicalId":44178,"journal":{"name":"Advances in Operations Research","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139757425","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}
In this review article, we consider discrete-time birth-death processes and their applications to discrete-time queues. To make the analysis simpler to follow, we focus on transform-free methods and consider instances of non-birth-death Markovian discrete-time systems. We present a number of results within one discrete-time framework that parallels the treatment of continuous time models. This approach has two advantages; first, it unifies the treatment of several discrete-time models in one framework, and second, it parallels to the extent possible the treatment of continuous time models. This allows us to draw parallels and contrasts between the discrete and continuous time queues. Specifically, we focus on birth-death applications to the single server discrete-time model with Bernoulli arrivals and geometric service times and provide the reader with a simple rigorous detailed analysis that covers all five scheduling rules considered in the literature, with attention to stationary distributions at slot edges, slot centers, and prearrival epochs. We also cover the waiting time distributions. Moreover, we cover three Markovian models that fit the global balance equations. Our approach provides interesting insights into the behavior of discrete-time queues. The article is intended for those who are familiar with queueing theory basics and would like a simple, yet rigorous introductory treatment to discrete-time queues.
{"title":"A Review of Birth-Death and Other Markovian Discrete-Time Queues","authors":"Muhammad El-Taha","doi":"10.1155/2023/6620393","DOIUrl":"https://doi.org/10.1155/2023/6620393","url":null,"abstract":"In this review article, we consider discrete-time birth-death processes and their applications to discrete-time queues. To make the analysis simpler to follow, we focus on transform-free methods and consider instances of non-birth-death Markovian discrete-time systems. We present a number of results within one discrete-time framework that parallels the treatment of continuous time models. This approach has two advantages; first, it unifies the treatment of several discrete-time models in one framework, and second, it parallels to the extent possible the treatment of continuous time models. This allows us to draw parallels and contrasts between the discrete and continuous time queues. Specifically, we focus on birth-death applications to the single server discrete-time model with Bernoulli arrivals and geometric service times and provide the reader with a simple rigorous detailed analysis that covers all five scheduling rules considered in the literature, with attention to stationary distributions at slot edges, slot centers, and prearrival epochs. We also cover the waiting time distributions. Moreover, we cover three Markovian models that fit the global balance equations. Our approach provides interesting insights into the behavior of discrete-time queues. The article is intended for those who are familiar with queueing theory basics and would like a simple, yet rigorous introductory treatment to discrete-time queues.","PeriodicalId":44178,"journal":{"name":"Advances in Operations Research","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138504866","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}
Agaraoli Aravazhi, Berit I. Helgheim, Petter Aadahl
This paper investigates predictive process monitoring problems in emergency treatment by combining the fields of process management and artificial intelligence. The objective is to predict the next activity and its timestamp in the treatment of emergency patients who have undergone surgery at the gastroenterology or urology surgery units in a hospital in Norway. To achieve this goal, three models were developed using different algorithms, and the best performing model was identified using various performance metrics. The results demonstrate the potential of predictive process monitoring to accurately forecast the outcome of patient treatments. By leveraging the insights gained from predictive process monitoring, hospitals can make more informed decisions. The findings of this study suggest that predictive process monitoring holds significant promise as a tool for improving the efficiency and effectiveness of emergency patient treatment processes. This research has significant implications for the field of decision sciences, particularly regarding resource allocation, reducing waiting times, and improving patient outcomes. The ability to predict the outcomes of patient treatment processes has important implications for hospitals, allowing the streamlining and acceleration of the treatment process. Overall, this study provides a promising framework for predicting patient treatment processes by using the predictive process monitoring method. This could be expanded upon in future research, ultimately leading to improved patient outcomes and better decision-making in healthcare.
{"title":"Decision-Making Based on Predictive Process Monitoring of Patient Treatment Processes: A Case Study of Emergency Patients","authors":"Agaraoli Aravazhi, Berit I. Helgheim, Petter Aadahl","doi":"10.1155/2023/8867057","DOIUrl":"https://doi.org/10.1155/2023/8867057","url":null,"abstract":"This paper investigates predictive process monitoring problems in emergency treatment by combining the fields of process management and artificial intelligence. The objective is to predict the next activity and its timestamp in the treatment of emergency patients who have undergone surgery at the gastroenterology or urology surgery units in a hospital in Norway. To achieve this goal, three models were developed using different algorithms, and the best performing model was identified using various performance metrics. The results demonstrate the potential of predictive process monitoring to accurately forecast the outcome of patient treatments. By leveraging the insights gained from predictive process monitoring, hospitals can make more informed decisions. The findings of this study suggest that predictive process monitoring holds significant promise as a tool for improving the efficiency and effectiveness of emergency patient treatment processes. This research has significant implications for the field of decision sciences, particularly regarding resource allocation, reducing waiting times, and improving patient outcomes. The ability to predict the outcomes of patient treatment processes has important implications for hospitals, allowing the streamlining and acceleration of the treatment process. Overall, this study provides a promising framework for predicting patient treatment processes by using the predictive process monitoring method. This could be expanded upon in future research, ultimately leading to improved patient outcomes and better decision-making in healthcare.","PeriodicalId":44178,"journal":{"name":"Advances in Operations Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135345112","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 aim of this article is to analyze the scientific developments in public sector decision making during the period 2010–2020, to identify which decision-making methods are preferred in different sectors of the public sector, and to determine which integrated methods are applied in this sector. In total, 468 scholarly articles were selected covering a near comprehensive review of the literature, as described below in the search process. We found that 271studies utilized a single method, whereas 180 studies utilized integrated methods. Data envelopment analysis (DEA) was the most common, used by 97 studies. However, an analytic hierarchy process (AHP) was utilized by 178 studies when counting both simple and integrated methods. It was shown that single methods were more commonly used in education, environment, health, and public services, and integrated methods were relatively favored in economics/finance, energy, site selection, and waste management. We conclude that multiple decision-making methods are used in the public sector, and during2010–2020, there has been a tendency to use unified methods in decision-making processes.
{"title":"Decision-Making Methods in the Public Sector during 2010–2020: A Systematic Review","authors":"Christina Fountzoula, Konstantinos Aravossis","doi":"10.1155/2022/1750672","DOIUrl":"https://doi.org/10.1155/2022/1750672","url":null,"abstract":"The aim of this article is to analyze the scientific developments in public sector decision making during the period 2010–2020, to identify which decision-making methods are preferred in different sectors of the public sector, and to determine which integrated methods are applied in this sector. In total, 468 scholarly articles were selected covering a near comprehensive review of the literature, as described below in the search process. We found that 271studies utilized a single method, whereas 180 studies utilized integrated methods. Data envelopment analysis (DEA) was the most common, used by 97 studies. However, an analytic hierarchy process (AHP) was utilized by 178 studies when counting both simple and integrated methods. It was shown that single methods were more commonly used in education, environment, health, and public services, and integrated methods were relatively favored in economics/finance, energy, site selection, and waste management. We conclude that multiple decision-making methods are used in the public sector, and during2010–2020, there has been a tendency to use unified methods in decision-making processes.","PeriodicalId":44178,"journal":{"name":"Advances in Operations Research","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138543684","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}
Hugo Monzón Maldonado, H. Aguirre, S. Vérel, A. Liefooghe, B. Derbel, Kiyoshi Tanaka
Achieving a high-resolution approximation and hitting the Pareto optimal set with some if not all members of the population is the goal for multi- and many-objective optimization problems, and more so in real-world applications where there is also the desire to extract knowledge about the problem from this set. The task requires not only to reach the Pareto optimal set but also to be able to continue discovering new solutions, even if the population is filled with them. Particularly in many-objective problems where the population may not be able to accommodate the full Pareto optimal set. In this work, our goal is to investigate some tools to understand the behavior of algorithms once they converge and how their population size and particularities of their selection mechanism aid or hinder their ability to keep finding optimal solutions. Through the use of features that look into the population composition during the search process, we will look into the algorithm’s behavior and dynamics and extract some insights. Features are defined in terms of dominance status, membership to the Pareto optimal set, recentness of discovery, and replacement of optimal solutions. Complementing the study with features, we also look at the approximation through the accumulated number of Pareto optimal solutions found and its relationship to a common metric, the hypervolume. To generate the data for analysis, the chosen problem is MNK-landscapes with settings that make it easy to converge, enumerable for instances with 3 to 6 objectives. Studied algorithms were selected from representative multi- and many-objective optimization approaches such as Pareto dominance, relaxation of Pareto dominance, indicator-based, and decomposition.
{"title":"Understanding Population Dynamics in Multi- and Many-Objective Evolutionary Algorithms for High-Resolution Approximations","authors":"Hugo Monzón Maldonado, H. Aguirre, S. Vérel, A. Liefooghe, B. Derbel, Kiyoshi Tanaka","doi":"10.1155/2021/6699277","DOIUrl":"https://doi.org/10.1155/2021/6699277","url":null,"abstract":"Achieving a high-resolution approximation and hitting the Pareto optimal set with some if not all members of the population is the goal for multi- and many-objective optimization problems, and more so in real-world applications where there is also the desire to extract knowledge about the problem from this set. The task requires not only to reach the Pareto optimal set but also to be able to continue discovering new solutions, even if the population is filled with them. Particularly in many-objective problems where the population may not be able to accommodate the full Pareto optimal set. In this work, our goal is to investigate some tools to understand the behavior of algorithms once they converge and how their population size and particularities of their selection mechanism aid or hinder their ability to keep finding optimal solutions. Through the use of features that look into the population composition during the search process, we will look into the algorithm’s behavior and dynamics and extract some insights. Features are defined in terms of dominance status, membership to the Pareto optimal set, recentness of discovery, and replacement of optimal solutions. Complementing the study with features, we also look at the approximation through the accumulated number of Pareto optimal solutions found and its relationship to a common metric, the hypervolume. To generate the data for analysis, the chosen problem is MNK-landscapes with settings that make it easy to converge, enumerable for instances with 3 to 6 objectives. Studied algorithms were selected from representative multi- and many-objective optimization approaches such as Pareto dominance, relaxation of Pareto dominance, indicator-based, and decomposition.","PeriodicalId":44178,"journal":{"name":"Advances in Operations Research","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2021-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44556977","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}
Oil industry in India has entered the competitive world, and each organization used probing strategies to reduce cost. India is a non-oil-producing country, and the scope for this lies in reducing supply chain cost in downstream logistics. This research provides an integrated model of key enablers for transporter’s performance in downstream logistics excellence of Indian oil sector to provide oil marketing companies’ a direction for design of future strategies to reduce downstream logistics cost. The sequential mixed-methods design is adopted. It identifies the enablers through literature review and interviews with transporters, working managers, and logistics experts (qualitative), and then, interpretive structural modeling (ISM) and MICMAC analysis (quantitative) are used to develop the diagraph and matrix to establish the contextual relationship and find their role and influence on each other. This readymade, unique, and unified model provides enablers for transporters’ performance in different individual categories, namely, dependent, independent, and autonomous enablers, and link them based on their driving power and dependence power along with their influencing behavior to enable transporters, working managers, and top management to focus on for reducing the logistics cost and shall add value for the ultimate customers. The academicians shall be benefited by appreciating practical aspects of this business.
{"title":"Modeling Enablers of Transporter’s Performance in Downstream Logistics of the Indian Oil Sector","authors":"R. Malik, M. Srivastava, Imlak Shaikh","doi":"10.1155/2021/1654326","DOIUrl":"https://doi.org/10.1155/2021/1654326","url":null,"abstract":"Oil industry in India has entered the competitive world, and each organization used probing strategies to reduce cost. India is a non-oil-producing country, and the scope for this lies in reducing supply chain cost in downstream logistics. This research provides an integrated model of key enablers for transporter’s performance in downstream logistics excellence of Indian oil sector to provide oil marketing companies’ a direction for design of future strategies to reduce downstream logistics cost. The sequential mixed-methods design is adopted. It identifies the enablers through literature review and interviews with transporters, working managers, and logistics experts (qualitative), and then, interpretive structural modeling (ISM) and MICMAC analysis (quantitative) are used to develop the diagraph and matrix to establish the contextual relationship and find their role and influence on each other. This readymade, unique, and unified model provides enablers for transporters’ performance in different individual categories, namely, dependent, independent, and autonomous enablers, and link them based on their driving power and dependence power along with their influencing behavior to enable transporters, working managers, and top management to focus on for reducing the logistics cost and shall add value for the ultimate customers. The academicians shall be benefited by appreciating practical aspects of this business.","PeriodicalId":44178,"journal":{"name":"Advances in Operations Research","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2021-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43606351","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}
Overcrowding of emergency departments (EDs) is a problem that affected many hospitals especially during the response to emergency situations such as pandemics or disasters. Transferring nonemergency patients is one approach that can be utilized to address ED overcrowding. We propose a novel mixed-integer nonlinear programming (MINLP) model that explicitly considers queueing effects to address overcrowding in a network of EDs, via a combination of two decisions: modifying service capacity to EDs and transferring patients between EDs. Computational testing is performed using a Design of Experiments to determine the sensitivity of the MINLP solutions to changes in the various input parameters. Additional computational testing examines the effect of ED size on the number of transfers occurring in the system, identifying an efficient frontier for the tradeoff between system cost (measured as a function of the service capacity and the number of patient transfers) and the systemwide average expected waiting time. Taken together, these results suggest that our optimization model can identify a range of efficient alternatives for healthcare systems designing a network of EDs across multiple hospitals.
{"title":"An Optimization Model to Address Overcrowding in Emergency Departments Using Patient Transfer","authors":"Zeynab Oveysi, Ronald G. McGarvey, Kangwon Seo","doi":"10.1155/2021/7120291","DOIUrl":"https://doi.org/10.1155/2021/7120291","url":null,"abstract":"Overcrowding of emergency departments (EDs) is a problem that affected many hospitals especially during the response to emergency situations such as pandemics or disasters. Transferring nonemergency patients is one approach that can be utilized to address ED overcrowding. We propose a novel mixed-integer nonlinear programming (MINLP) model that explicitly considers queueing effects to address overcrowding in a network of EDs, via a combination of two decisions: modifying service capacity to EDs and transferring patients between EDs. Computational testing is performed using a Design of Experiments to determine the sensitivity of the MINLP solutions to changes in the various input parameters. Additional computational testing examines the effect of ED size on the number of transfers occurring in the system, identifying an efficient frontier for the tradeoff between system cost (measured as a function of the service capacity and the number of patient transfers) and the systemwide average expected waiting time. Taken together, these results suggest that our optimization model can identify a range of efficient alternatives for healthcare systems designing a network of EDs across multiple hospitals.","PeriodicalId":44178,"journal":{"name":"Advances in Operations Research","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44886996","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}
This paper deals with the stationary analysis of a fluid queue driven by an queueing model subject to Bernoulli-Schedule-Controlled Vacation and Vacation Interruption. The model under consideration can be viewed as a quasi-birth and death process. The governing system of differential difference equations is solved using matrix-geometric method in the Laplacian domain. The resulting solutions are then inverted to obtain an explicit expression for the joint steady state probabilities of the content of the buffer and the state of the background queueing model. Numerical illustrations are added to depict the convergence of the stationary buffer content distribution to one subject to suitable stability conditions.
{"title":"Fluid Queue Driven by an Queue Subject to Bernoulli-Schedule-Controlled Vacation and Vacation Interruption","authors":"K. V. Vijayashree, Atlimuthu Anjuka","doi":"10.1155/2016/2673017","DOIUrl":"https://doi.org/10.1155/2016/2673017","url":null,"abstract":"This paper deals with the stationary analysis of a fluid queue driven by an queueing model subject to Bernoulli-Schedule-Controlled Vacation and Vacation Interruption. The model under consideration can be viewed as a quasi-birth and death process. The governing system of differential difference equations is solved using matrix-geometric method in the Laplacian domain. The resulting solutions are then inverted to obtain an explicit expression for the joint steady state probabilities of the content of the buffer and the state of the background queueing model. Numerical illustrations are added to depict the convergence of the stationary buffer content distribution to one subject to suitable stability conditions.","PeriodicalId":44178,"journal":{"name":"Advances in Operations Research","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2016-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2016/2673017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64290266","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}
Shabnam Mohammadi Ardakani, Hamid Babaei Meybodi, H. S. Tooranloo
Data Envelopment Analysis is a powerful tool for evaluating the efficiency of decision-making units for the purpose of ranking, comparing, and differentiating efficient and inefficient units. Classical Data Envelopment Analysis methods operate by measuring the efficiency of each DMU compared to similar units without considering their internal workings and structures, which make them unsuitable for cases where DMUs are multistaged processes with intermediate products or when inputs and outputs are ambiguous or nonconfigurable. In problems that involve uncertainty, intuitionistic fuzzy sets can offer a better representation and interpretation of information than classic sets. In this paper, the noncooperative network data envelopment analysis model of Liang et al. (2008), which is based on Stackelberg game theory and efficiency decomposition, is expanded using the concepts of best and worst relative returns Data Envelopment Analysis model of Azizi et al. (2013) into an interval efficiency estimation model with α-β cuts for two-stage DMUs with trapezoidal intuitionistic fuzzy data. Furthermore, the method of Yue (2011) is used to rank these DMUs in terms of their intuitionistic fuzzy interval efficiency. A numerical example is also provided to illustrate the application of the proposed bounded two-stage intuitionistic Data Envelopment Analysis model.
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