In the field of operation research, both linear and fractional programming problems have been more encountered in recent years because they are more realistic in expressing real-life problems. Fractional programming problem is used when several rates need to be optimized simultaneously such as resource allocation planning, financial and corporate planning, healthcare, and hospital planning. There are several techniques to solve the multiobjective linear fractional programming problem. However, because of the use of scalarization, these techniques have some limitations. This paper proposed two new mean and median techniques to solve the multiobjective linear fractional programming problem by overcoming the limitations. After utilizing mean and median techniques, the problem is converted into an equivalent linear fractional programming problem; then, the linear fractional programming problem is transformed into linear programming problem and solved by the conventional simplex method or mathematical software. Some numerical examples have been illustrated to show the efficiency of the proposed techniques and algorithm. The performance of these solutions was evaluated by comparing their results with other existing methods. The numerical results have shown that the proposed techniques are better than other techniques. Furthermore, the proposed techniques solve a pure multiobjective maximization problem, which is even impossible with some existing techniques. The present investigation can be improved further, which is left for future research.
{"title":"New Mean and Median Techniques to Solve Multiobjective Linear Fractional Programming Problem and Comparison with Other Techniques","authors":"Getaye Fentaw, Adane Akate","doi":"10.1155/2024/5000269","DOIUrl":"https://doi.org/10.1155/2024/5000269","url":null,"abstract":"In the field of operation research, both linear and fractional programming problems have been more encountered in recent years because they are more realistic in expressing real-life problems. Fractional programming problem is used when several rates need to be optimized simultaneously such as resource allocation planning, financial and corporate planning, healthcare, and hospital planning. There are several techniques to solve the multiobjective linear fractional programming problem. However, because of the use of scalarization, these techniques have some limitations. This paper proposed two new mean and median techniques to solve the multiobjective linear fractional programming problem by overcoming the limitations. After utilizing mean and median techniques, the problem is converted into an equivalent linear fractional programming problem; then, the linear fractional programming problem is transformed into linear programming problem and solved by the conventional simplex method or mathematical software. Some numerical examples have been illustrated to show the efficiency of the proposed techniques and algorithm. The performance of these solutions was evaluated by comparing their results with other existing methods. The numerical results have shown that the proposed techniques are better than other techniques. Furthermore, the proposed techniques solve a pure multiobjective maximization problem, which is even impossible with some existing techniques. The present investigation can be improved further, which is left for future research.","PeriodicalId":42964,"journal":{"name":"Journal of Optimization","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141007894","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}
N. Vaegae, Visalakshi Annepu, Kalapraveen Bagadi, Fadl Dahan
As smart cities expand rapidly, the demand for strong fire protection has become even more essential. A significant challenge lies in ensuring that fire detection systems integrate seamlessly into our modern infrastructures. Leveraging multisensor systems can yield reliable data on potential fires. Particularly in smart buildings, the effectiveness of multisensor fire detection algorithms becomes paramount. This research introduces a fuzzy logic-driven method that harnesses the power of smoke, flame, and temperature sensors. While smoke, flames, and elevated temperatures are primary fire indicators, they can manifest concurrently or sequentially. We have amalgamated various fuzzy logic rules (IF-THEN structures) to gauge the intensity of fires. When a fire ignites, the sensors spring into action, identifying its source and promptly notifying users via the Internet and GSM modems. Moreover, they relay the fire’s precise geographic coordinates to fire departments. The fire’s status will be consistently updated on a dedicated online portal. It was observed from our results that the system proficiently sends fire alerts to residents, and the fire status undergoes regular updates at 45-second intervals. This refreshing is initiated by the identification of a designated percentage of smoke and flame. These outcomes validate the system’s effectiveness in enhancing the precision and responsiveness of fire detection capabilities.
{"title":"Multisensor Fuzzy Logic Approach for Enhanced Fire Detection in Smart Cities","authors":"N. Vaegae, Visalakshi Annepu, Kalapraveen Bagadi, Fadl Dahan","doi":"10.1155/2024/8511649","DOIUrl":"https://doi.org/10.1155/2024/8511649","url":null,"abstract":"As smart cities expand rapidly, the demand for strong fire protection has become even more essential. A significant challenge lies in ensuring that fire detection systems integrate seamlessly into our modern infrastructures. Leveraging multisensor systems can yield reliable data on potential fires. Particularly in smart buildings, the effectiveness of multisensor fire detection algorithms becomes paramount. This research introduces a fuzzy logic-driven method that harnesses the power of smoke, flame, and temperature sensors. While smoke, flames, and elevated temperatures are primary fire indicators, they can manifest concurrently or sequentially. We have amalgamated various fuzzy logic rules (IF-THEN structures) to gauge the intensity of fires. When a fire ignites, the sensors spring into action, identifying its source and promptly notifying users via the Internet and GSM modems. Moreover, they relay the fire’s precise geographic coordinates to fire departments. The fire’s status will be consistently updated on a dedicated online portal. It was observed from our results that the system proficiently sends fire alerts to residents, and the fire status undergoes regular updates at 45-second intervals. This refreshing is initiated by the identification of a designated percentage of smoke and flame. These outcomes validate the system’s effectiveness in enhancing the precision and responsiveness of fire detection capabilities.","PeriodicalId":42964,"journal":{"name":"Journal of Optimization","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140233736","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 study shows that refrigerants R1234ze (E) and R1234ze (Z), known for their low global warming potential, are likely to become primary choices in heat pump air conditioning for residential and commercial use. The research evaluates the thermodynamic properties of R1234ze (Z) using experimental, thermodynamic, and numerical analyses. It addresses F-gas regulation requirements and aligns with the Paris Agreement goals by exploring various refrigerants, including R227ea, R114, R236fa, R134a, R1234ze (Z), and R245fa, as potential candidates for evolving industry needs. The analysis indicates that R1234ze (Z) outperforms other working fluids in heat pump applications, with an optimized theoretical coefficient of performance (COP) at a condensation temperature 22 K lower than critical temperatures. However, actual COP deviates due to a significant pressure drop, especially with inadequate volumetric capacity. A key finding is that a substantial portion of the pressure reduction is attributed to mitigating irreversible losses, estimated at a condensation temperature of 70–75°C, emphasizing the complex relationship between pressure and performance. The study suggests that R1234ze (Z) is more suitable for high-temperature applications than traditional air conditioning systems. In a parallel assessment, the initial calculation of the coefficient of performance for R245fa evaluates the reliability of a new refrigeration industry arrangement. Test results for heat pump technology reveal that R1234ze (Z) achieves an impressive COP of up to 3.60 at a buildup temperature of 90°C with a temperature differential of 45 K. This positions R1234ze (Z) as a suitable choice for heat pump applications prioritizing simplicity in system design.
{"title":"Performance of Heat Pump Air Conditioning with R1234ze (HFO) as a Refrigerant","authors":"Subhash Kumar, V. Raibhole, Himadri Majumder","doi":"10.1155/2024/9101945","DOIUrl":"https://doi.org/10.1155/2024/9101945","url":null,"abstract":"The study shows that refrigerants R1234ze (E) and R1234ze (Z), known for their low global warming potential, are likely to become primary choices in heat pump air conditioning for residential and commercial use. The research evaluates the thermodynamic properties of R1234ze (Z) using experimental, thermodynamic, and numerical analyses. It addresses F-gas regulation requirements and aligns with the Paris Agreement goals by exploring various refrigerants, including R227ea, R114, R236fa, R134a, R1234ze (Z), and R245fa, as potential candidates for evolving industry needs. The analysis indicates that R1234ze (Z) outperforms other working fluids in heat pump applications, with an optimized theoretical coefficient of performance (COP) at a condensation temperature 22 K lower than critical temperatures. However, actual COP deviates due to a significant pressure drop, especially with inadequate volumetric capacity. A key finding is that a substantial portion of the pressure reduction is attributed to mitigating irreversible losses, estimated at a condensation temperature of 70–75°C, emphasizing the complex relationship between pressure and performance. The study suggests that R1234ze (Z) is more suitable for high-temperature applications than traditional air conditioning systems. In a parallel assessment, the initial calculation of the coefficient of performance for R245fa evaluates the reliability of a new refrigeration industry arrangement. Test results for heat pump technology reveal that R1234ze (Z) achieves an impressive COP of up to 3.60 at a buildup temperature of 90°C with a temperature differential of 45 K. This positions R1234ze (Z) as a suitable choice for heat pump applications prioritizing simplicity in system design.","PeriodicalId":42964,"journal":{"name":"Journal of Optimization","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139846389","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 study shows that refrigerants R1234ze (E) and R1234ze (Z), known for their low global warming potential, are likely to become primary choices in heat pump air conditioning for residential and commercial use. The research evaluates the thermodynamic properties of R1234ze (Z) using experimental, thermodynamic, and numerical analyses. It addresses F-gas regulation requirements and aligns with the Paris Agreement goals by exploring various refrigerants, including R227ea, R114, R236fa, R134a, R1234ze (Z), and R245fa, as potential candidates for evolving industry needs. The analysis indicates that R1234ze (Z) outperforms other working fluids in heat pump applications, with an optimized theoretical coefficient of performance (COP) at a condensation temperature 22 K lower than critical temperatures. However, actual COP deviates due to a significant pressure drop, especially with inadequate volumetric capacity. A key finding is that a substantial portion of the pressure reduction is attributed to mitigating irreversible losses, estimated at a condensation temperature of 70–75°C, emphasizing the complex relationship between pressure and performance. The study suggests that R1234ze (Z) is more suitable for high-temperature applications than traditional air conditioning systems. In a parallel assessment, the initial calculation of the coefficient of performance for R245fa evaluates the reliability of a new refrigeration industry arrangement. Test results for heat pump technology reveal that R1234ze (Z) achieves an impressive COP of up to 3.60 at a buildup temperature of 90°C with a temperature differential of 45 K. This positions R1234ze (Z) as a suitable choice for heat pump applications prioritizing simplicity in system design.
{"title":"Performance of Heat Pump Air Conditioning with R1234ze (HFO) as a Refrigerant","authors":"Subhash Kumar, V. Raibhole, Himadri Majumder","doi":"10.1155/2024/9101945","DOIUrl":"https://doi.org/10.1155/2024/9101945","url":null,"abstract":"The study shows that refrigerants R1234ze (E) and R1234ze (Z), known for their low global warming potential, are likely to become primary choices in heat pump air conditioning for residential and commercial use. The research evaluates the thermodynamic properties of R1234ze (Z) using experimental, thermodynamic, and numerical analyses. It addresses F-gas regulation requirements and aligns with the Paris Agreement goals by exploring various refrigerants, including R227ea, R114, R236fa, R134a, R1234ze (Z), and R245fa, as potential candidates for evolving industry needs. The analysis indicates that R1234ze (Z) outperforms other working fluids in heat pump applications, with an optimized theoretical coefficient of performance (COP) at a condensation temperature 22 K lower than critical temperatures. However, actual COP deviates due to a significant pressure drop, especially with inadequate volumetric capacity. A key finding is that a substantial portion of the pressure reduction is attributed to mitigating irreversible losses, estimated at a condensation temperature of 70–75°C, emphasizing the complex relationship between pressure and performance. The study suggests that R1234ze (Z) is more suitable for high-temperature applications than traditional air conditioning systems. In a parallel assessment, the initial calculation of the coefficient of performance for R245fa evaluates the reliability of a new refrigeration industry arrangement. Test results for heat pump technology reveal that R1234ze (Z) achieves an impressive COP of up to 3.60 at a buildup temperature of 90°C with a temperature differential of 45 K. This positions R1234ze (Z) as a suitable choice for heat pump applications prioritizing simplicity in system design.","PeriodicalId":42964,"journal":{"name":"Journal of Optimization","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139786525","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}
Background. Food provides the required nutrients for adequate growth and development. However, meeting the recommended nutrients while considering environmental sustainability can be complicated and challenging. Previously, trial-and-error methods were used for product development, but these are tedious and time-consuming. Mathematical techniques such as linear programming offer an alternative and rapid approach to developing products with nutritional/or sustainability considerations. This method has been extensively used in diet optimisation but does not sufficiently address dietary problems with more than one objective function. Aim. The review aimed to explore the extent of mathematical approaches to address dietary problems. Methodology. A systematic review approach was adopted for the research. The major search engines used were Scopus, PubMed, and Science Direct, based on selected keywords. A stepwise structural method was used to obtain articles. Articles that contained the search keywords but applied in nonhuman cases were excluded. Duplicated articles were also excluded and accounted for as one. All articles were subjected to further review based on their abstract and complete titles before passing them for data analysis. Results. The total number of articles obtained from the search activity was 280. Fifty-six were retained after the criteria for inclusion were applied to them. Out of the 56 articles retained, only two studies used goal programming and nonlinear generalised mathematical approaches to address dietary problems. All other studies used the linear programming approach, focusing mainly on one or two constraints (nutrients and/or acceptability), highlighting the limitations of linear programming in addressing the multiple factors of a sustainable diet. Several researchers have proposed using multiobjective optimisation, an extension of linear programming, to address challenges with sustainable diets. These approaches can be further explored to address sustainable dietary problems.
{"title":"A Systematic Review of Linear Programming Techniques as Applied to Diet Optimisation and Opportunities for Improvement","authors":"Leticia Donkor, Emmanuel Essien, N. S. Affrifah","doi":"10.1155/2023/1271115","DOIUrl":"https://doi.org/10.1155/2023/1271115","url":null,"abstract":"Background. Food provides the required nutrients for adequate growth and development. However, meeting the recommended nutrients while considering environmental sustainability can be complicated and challenging. Previously, trial-and-error methods were used for product development, but these are tedious and time-consuming. Mathematical techniques such as linear programming offer an alternative and rapid approach to developing products with nutritional/or sustainability considerations. This method has been extensively used in diet optimisation but does not sufficiently address dietary problems with more than one objective function. Aim. The review aimed to explore the extent of mathematical approaches to address dietary problems. Methodology. A systematic review approach was adopted for the research. The major search engines used were Scopus, PubMed, and Science Direct, based on selected keywords. A stepwise structural method was used to obtain articles. Articles that contained the search keywords but applied in nonhuman cases were excluded. Duplicated articles were also excluded and accounted for as one. All articles were subjected to further review based on their abstract and complete titles before passing them for data analysis. Results. The total number of articles obtained from the search activity was 280. Fifty-six were retained after the criteria for inclusion were applied to them. Out of the 56 articles retained, only two studies used goal programming and nonlinear generalised mathematical approaches to address dietary problems. All other studies used the linear programming approach, focusing mainly on one or two constraints (nutrients and/or acceptability), highlighting the limitations of linear programming in addressing the multiple factors of a sustainable diet. Several researchers have proposed using multiobjective optimisation, an extension of linear programming, to address challenges with sustainable diets. These approaches can be further explored to address sustainable dietary problems.","PeriodicalId":42964,"journal":{"name":"Journal of Optimization","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78340362","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}
Continuous extrusion (CE) is a method of creating endless profiles of high-quality products of dimensional accurateness, high productivity, and excellent material properties. The main objective of this study is to investigate the influence of CE input process parameters on optimal overall extrusion load requirement and effective stress induced. The input parameters considered were extrusion driving wheel speed, feed metal temperature, tool temperature, and factor of friction proceeding. Numerical simulations of a copper alloy (C18150) were carried out using DEFORM-3D to investigate the impact of the input variables on total load and effective stresses. A mathematical model based on response surface methodology (RSM) was developed for optimized results. The optimized parameters in terms of wheel extrusion velocities, feedstock temperatures, tool temperatures, and friction factors expressed. The ANOVA test was performed to assess the suitability and appropriateness of the model. Using RSM, the optimal load value of 408.167 kN and effective stress of 1241.0 MPa were achieved within the composite preference of 1.0. A load of 408.167 kN had been obtained if the velocity of the wheel, temperatures of feedstock, tool temperatures, and factors of friction are 4 rpm, 500°C, 400°C, and 0.85, respectively. The minimum effective stress of 1241.0 MPa is induced in the feedstock due to the CE process if the velocity of the wheel, temperature of the feedstock, die temperature, and frictional factor were 4 rpm, 500°C, 400°C, and 0.95, respectively.
{"title":"Optimization of Deformation Behaviors during Continuous Forming Extrusion of C18150 Copper Alloy through Response Surface Methodology","authors":"Tariku Desta, D. Sinha, P. J. Ramulu","doi":"10.1155/2023/6682884","DOIUrl":"https://doi.org/10.1155/2023/6682884","url":null,"abstract":"Continuous extrusion (CE) is a method of creating endless profiles of high-quality products of dimensional accurateness, high productivity, and excellent material properties. The main objective of this study is to investigate the influence of CE input process parameters on optimal overall extrusion load requirement and effective stress induced. The input parameters considered were extrusion driving wheel speed, feed metal temperature, tool temperature, and factor of friction proceeding. Numerical simulations of a copper alloy (C18150) were carried out using DEFORM-3D to investigate the impact of the input variables on total load and effective stresses. A mathematical model based on response surface methodology (RSM) was developed for optimized results. The optimized parameters in terms of wheel extrusion velocities, feedstock temperatures, tool temperatures, and friction factors expressed. The ANOVA test was performed to assess the suitability and appropriateness of the model. Using RSM, the optimal load value of 408.167 kN and effective stress of 1241.0 MPa were achieved within the composite preference of 1.0. A load of 408.167 kN had been obtained if the velocity of the wheel, temperatures of feedstock, tool temperatures, and factors of friction are 4 rpm, 500°C, 400°C, and 0.85, respectively. The minimum effective stress of 1241.0 MPa is induced in the feedstock due to the CE process if the velocity of the wheel, temperature of the feedstock, die temperature, and frictional factor were 4 rpm, 500°C, 400°C, and 0.95, respectively.","PeriodicalId":42964,"journal":{"name":"Journal of Optimization","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83087555","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}
Miriam Appiah-Brempong, Helen Michelle Korkor Essandoh, Nana Yaw Asiedu, Samuel Kwame Dadzie, Francis Warings Yao Momade
Vegetable tannery wastewater, highly laden with recalcitrant organics, is not easily treatable through biological processes. This study focuses on the use of response surface methodology in optimizing a coagulation-flocculation process for pretreatment of vegetable tannery wastewater. This study also assessed the possibility of replacing chemical coagulants such as aluminum sulphate with green alternatives such as cassava starch and orange peel powder. The effects of coagulant dosage and pH on three key wastewater quality parameters (chemical oxygen demand (COD) and total suspended solids (TSS)’s removal efficiencies as well as sludge volume index (SVI)) were also assessed. Quadratic models developed for all the three responses were adequate. The optimal conditions were attained at a pH of 3.17 and a dosage of 2.76 g/L for cassava starch coagulant, pH of 3.74 and a dosage of 5.16 g/L for orange peel powder coagulant, and pH of 6.09 and a dosage of 11.60 g/L for aluminum sulphate. The COD and TSS removal efficiencies as well as SVI achieved under these optimal conditions were 37.25%, 73.95%, and 14.80 mL/g, respectively, for cassava starch coagulant; 17.97%, 66.08%, and 19.87 mL/g, respectively, for orange peel powder coagulant; and 38.51%, 76.06%, and 29.57 mL/g, respectively, for aluminum sulphate. The outperformance of cassava starch over orange peel powder and its comparable results with aluminum sulphate makes the former a more environment-friendly alternative to aluminum sulphate for treatment of tannery wastewater.
{"title":"Performance Optimization of Chemical and Green Coagulants in Tannery Wastewater Treatment: A Response Surface Methodology Approach","authors":"Miriam Appiah-Brempong, Helen Michelle Korkor Essandoh, Nana Yaw Asiedu, Samuel Kwame Dadzie, Francis Warings Yao Momade","doi":"10.1155/2023/9939499","DOIUrl":"https://doi.org/10.1155/2023/9939499","url":null,"abstract":"Vegetable tannery wastewater, highly laden with recalcitrant organics, is not easily treatable through biological processes. This study focuses on the use of response surface methodology in optimizing a coagulation-flocculation process for pretreatment of vegetable tannery wastewater. This study also assessed the possibility of replacing chemical coagulants such as aluminum sulphate with green alternatives such as cassava starch and orange peel powder. The effects of coagulant dosage and pH on three key wastewater quality parameters (chemical oxygen demand (COD) and total suspended solids (TSS)’s removal efficiencies as well as sludge volume index (SVI)) were also assessed. Quadratic models developed for all the three responses were adequate. The optimal conditions were attained at a pH of 3.17 and a dosage of 2.76 g/L for cassava starch coagulant, pH of 3.74 and a dosage of 5.16 g/L for orange peel powder coagulant, and pH of 6.09 and a dosage of 11.60 g/L for aluminum sulphate. The COD and TSS removal efficiencies as well as SVI achieved under these optimal conditions were 37.25%, 73.95%, and 14.80 mL/g, respectively, for cassava starch coagulant; 17.97%, 66.08%, and 19.87 mL/g, respectively, for orange peel powder coagulant; and 38.51%, 76.06%, and 29.57 mL/g, respectively, for aluminum sulphate. The outperformance of cassava starch over orange peel powder and its comparable results with aluminum sulphate makes the former a more environment-friendly alternative to aluminum sulphate for treatment of tannery wastewater.","PeriodicalId":42964,"journal":{"name":"Journal of Optimization","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87046519","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}
Johnson Ramotsisi, Mompoloki Kgomotso, Lone Seboni
Purpose. Empirical studies on the topic of assigning university project students to supervisors are currently underexplored. Such studies are critical to success of both the students and the university. Whilst extant research on this topic has contributed to an understanding of student assignments, what appears to be missing is application of a comprehensive framework to inform formulation and validation of a robust solution approach that takes account of both student and supervisor preferences, to optimize a real-life student-to-project supervisor assignment problem. Methodology. Questionnaire and interview surveys with project coordinators, project supervisors, head of department and students were conducted to identify factors surrounding the student-to-project supervisor assignment, through a case study approach in a university department offering engineering degree programs. This study not only develops a framework to understand an effective student-to-project supervisor assignment decision but also applies it in practice, through a case study in a University department offering engineering degree programs. An integer linear programming model was developed and implemented in an optimization software to optimize the student-to-project supervisor assignment, using data from the case study. Findings. Using OpenSolver, validated model results show improvements in matching both students and project supervisors’ preferences, whilst complying with supervisors’ workloads. These results also reveal an improvement in minimizing the project coordinator’s time in doing the assignment by introducing a standardized approach that concurrently considers all variables in a consistent manner. Originality. The contribution lies in: (1) development of a robust framework for student-to-supervisor assignments, (2) explicit consideration of contextual factors that recognize different assignment scenarios, (3) identification of feedback loops to recognize not only the need for continuous improvement in student-to-supervisor assignments but also links to performance in final year projects, (4) unique insights to guide project coordinators in relation to an efficient, effective, comprehensive, and standardized approach to the student-to-project supervisor assignment, and (5) a deeper understanding of a comprehensive range of factors that play a role in student-to-project supervisor assignments in higher education institutions.
{"title":"An Optimization Model for the Student-to-Project Supervisor Assignment Problem-The Case of an Engineering Department","authors":"Johnson Ramotsisi, Mompoloki Kgomotso, Lone Seboni","doi":"10.1155/2022/9415210","DOIUrl":"https://doi.org/10.1155/2022/9415210","url":null,"abstract":"Purpose. Empirical studies on the topic of assigning university project students to supervisors are currently underexplored. Such studies are critical to success of both the students and the university. Whilst extant research on this topic has contributed to an understanding of student assignments, what appears to be missing is application of a comprehensive framework to inform formulation and validation of a robust solution approach that takes account of both student and supervisor preferences, to optimize a real-life student-to-project supervisor assignment problem. Methodology. Questionnaire and interview surveys with project coordinators, project supervisors, head of department and students were conducted to identify factors surrounding the student-to-project supervisor assignment, through a case study approach in a university department offering engineering degree programs. This study not only develops a framework to understand an effective student-to-project supervisor assignment decision but also applies it in practice, through a case study in a University department offering engineering degree programs. An integer linear programming model was developed and implemented in an optimization software to optimize the student-to-project supervisor assignment, using data from the case study. Findings. Using OpenSolver, validated model results show improvements in matching both students and project supervisors’ preferences, whilst complying with supervisors’ workloads. These results also reveal an improvement in minimizing the project coordinator’s time in doing the assignment by introducing a standardized approach that concurrently considers all variables in a consistent manner. Originality. The contribution lies in: (1) development of a robust framework for student-to-supervisor assignments, (2) explicit consideration of contextual factors that recognize different assignment scenarios, (3) identification of feedback loops to recognize not only the need for continuous improvement in student-to-supervisor assignments but also links to performance in final year projects, (4) unique insights to guide project coordinators in relation to an efficient, effective, comprehensive, and standardized approach to the student-to-project supervisor assignment, and (5) a deeper understanding of a comprehensive range of factors that play a role in student-to-project supervisor assignments in higher education institutions.","PeriodicalId":42964,"journal":{"name":"Journal of Optimization","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75190004","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}
A nine-compartment deterministic cholera model was formulated, and the model describes interactions between human, Vibrio cholerae bacteria, and the enviroment that warrant the interaction. Realities and socioeconomic burden influence spread and control mechanism of the disease. The model investigated some effective ways of hindering cholera outbreak and spread. The existence and uniqueness of solution of the system of equations that the model comprises were ascertained. The basic reproduction number R 0 of the model was obtained using “next-generation matrix” method, and the most sensitive parameters were identified using “normalised forward sensitivity index” method. Three controls, hygiene consciousness denoted by X1, cholera vaccine X2, and cholera awareness programme X3, were chosen. Optimal control theory is applied to ascertain the level of effect of the controls in reducing susceptible, exposed, infected individuals and causative pathogen population. Pontryagin’s maximum principle is used to prove the optimal solution of the model, and the optimal system was derived and numerically solved. Simulations were made with graphs that show the effects of the controls on susceptible, exposed, infected, and Vibrio cholerae population. The findings are that simultaneous application of the three controls can be one of the fast and effective ways of controlling cholera. If two controls are to be selected, hygiene consciousness and vaccine are the best combination.
{"title":"Optimal Control Analysis of Treatment Strategies of the Dynamics of Cholera","authors":"Sani Fakai Abubakar, M. Ibrahim","doi":"10.1155/2022/2314104","DOIUrl":"https://doi.org/10.1155/2022/2314104","url":null,"abstract":"A nine-compartment deterministic cholera model was formulated, and the model describes interactions between human, Vibrio cholerae bacteria, and the enviroment that warrant the interaction. Realities and socioeconomic burden influence spread and control mechanism of the disease. The model investigated some effective ways of hindering cholera outbreak and spread. The existence and uniqueness of solution of the system of equations that the model comprises were ascertained. The basic reproduction number \u0000 \u0000 \u0000 \u0000 R\u0000 \u0000 \u0000 0\u0000 \u0000 \u0000 \u0000 of the model was obtained using “next-generation matrix” method, and the most sensitive parameters were identified using “normalised forward sensitivity index” method. Three controls, hygiene consciousness denoted by X1, cholera vaccine X2, and cholera awareness programme X3, were chosen. Optimal control theory is applied to ascertain the level of effect of the controls in reducing susceptible, exposed, infected individuals and causative pathogen population. Pontryagin’s maximum principle is used to prove the optimal solution of the model, and the optimal system was derived and numerically solved. Simulations were made with graphs that show the effects of the controls on susceptible, exposed, infected, and Vibrio cholerae population. The findings are that simultaneous application of the three controls can be one of the fast and effective ways of controlling cholera. If two controls are to be selected, hygiene consciousness and vaccine are the best combination.","PeriodicalId":42964,"journal":{"name":"Journal of Optimization","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87592846","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}
Vahid Najafi moghaddam Gilani, Mohammad Reza Ghanbari Tamrin, S. Hosseinian, M. Nikookar, Daniel Safari, Soheil YektaParast
Nowadays, the performance analysis and evaluation of public transportation systems have great importance in traffic engineering science. So far, the bus system has not been very effective in some cities in Iran, and many management approaches such as the allocation of special lanes and regular bus scheduling, which are needed to increase the efficiency of this system, have not been sufficiently considered. The purpose of the present study is to optimize the delay of the signalized intersection of bus lane and investigate the factors affecting the urban bus usage by citizens in public transportation of Rasht city and especially their satisfaction. Therefore, the intersection delay was optimized by gathering the traffic volume data in peak hour time of a signalized intersection along the bus lane and using machine learning methods. In addition, by collecting two different questionnaires, taking 84 samples (first questionnaire) and 374 samples (second questionnaire), the satisfaction of citizens and business people on the boundary of the bus lane was considered. The results indicated that about 95% of the businesses around this route believe that the construction of the bus lane led to a decrease in the income of more than 110 dollars per month. Further to this, despite the lack of facilities, poorly designed routes, and lack of the bus system fleet, the bus lane of Imam Khomeini had a high degree of satisfaction among the citizens. The result of various models showed that the adaptive network-based fuzzy inference system (ANFIS) had the highest R2 and the lowest amount of root mean square error (RMSE). In fact, this model had a better performance to predict and optimize the delay of signalized intersection than the fuzzy model. The optimum amount of intersection delay was determined as 56 seconds. With this value, the delay of bus movements in the bus lane had a higher possibility of being reduced.
{"title":"Investigation of Bus Special Lane Performance Using Statistical Analysis and Optimization of the Signalized Intersection Delay by Machine Learning Methods","authors":"Vahid Najafi moghaddam Gilani, Mohammad Reza Ghanbari Tamrin, S. Hosseinian, M. Nikookar, Daniel Safari, Soheil YektaParast","doi":"10.1155/2022/2984803","DOIUrl":"https://doi.org/10.1155/2022/2984803","url":null,"abstract":"Nowadays, the performance analysis and evaluation of public transportation systems have great importance in traffic engineering science. So far, the bus system has not been very effective in some cities in Iran, and many management approaches such as the allocation of special lanes and regular bus scheduling, which are needed to increase the efficiency of this system, have not been sufficiently considered. The purpose of the present study is to optimize the delay of the signalized intersection of bus lane and investigate the factors affecting the urban bus usage by citizens in public transportation of Rasht city and especially their satisfaction. Therefore, the intersection delay was optimized by gathering the traffic volume data in peak hour time of a signalized intersection along the bus lane and using machine learning methods. In addition, by collecting two different questionnaires, taking 84 samples (first questionnaire) and 374 samples (second questionnaire), the satisfaction of citizens and business people on the boundary of the bus lane was considered. The results indicated that about 95% of the businesses around this route believe that the construction of the bus lane led to a decrease in the income of more than 110 dollars per month. Further to this, despite the lack of facilities, poorly designed routes, and lack of the bus system fleet, the bus lane of Imam Khomeini had a high degree of satisfaction among the citizens. The result of various models showed that the adaptive network-based fuzzy inference system (ANFIS) had the highest R2 and the lowest amount of root mean square error (RMSE). In fact, this model had a better performance to predict and optimize the delay of signalized intersection than the fuzzy model. The optimum amount of intersection delay was determined as 56 seconds. With this value, the delay of bus movements in the bus lane had a higher possibility of being reduced.","PeriodicalId":42964,"journal":{"name":"Journal of Optimization","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2022-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90418669","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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