Pub Date : 2022-07-26DOI: 10.11121/ijocta.2022.1146
Memduh Suveren, Rustu Akay, M. Kanaan
Wireless capsule endoscopy (WCE) is used for imaging and diagnosing diseases in the gastrointestinal (GI) system. The location of the disease detected by WCE is still an important problem. Location information is very important for the surgical or drug treatment of the detected disease. In this study, RSS-based centroid algorithm has been used in order to accurately predict the capsule position on a sample data set. The effect of different parameters such as number of sensors used on the proposed mathematical model, location of sensors on positioning is analyzed in detail. The results show that a precise position detection is possible with fewer sensors positioned correctly. As a result, the positioning error with the correctly selected sensors is reduced by approximately 55%. In addition, the performance of the proposed method was compared with the classical centroid algorithm and more than 50% improvement was achieved.
{"title":"Localization of an ultra wide band wireless endoscopy capsule inside the human body using received signal strength and centroid algorithm","authors":"Memduh Suveren, Rustu Akay, M. Kanaan","doi":"10.11121/ijocta.2022.1146","DOIUrl":"https://doi.org/10.11121/ijocta.2022.1146","url":null,"abstract":"Wireless capsule endoscopy (WCE) is used for imaging and diagnosing diseases in the gastrointestinal (GI) system. The location of the disease detected by WCE is still an important problem. Location information is very important for the surgical or drug treatment of the detected disease. In this study, RSS-based centroid algorithm has been used in order to accurately predict the capsule position on a sample data set. The effect of different parameters such as number of sensors used on the proposed mathematical model, location of sensors on positioning is analyzed in detail. The results show that a precise position detection is possible with fewer sensors positioned correctly. As a result, the positioning error with the correctly selected sensors is reduced by approximately 55%. In addition, the performance of the proposed method was compared with the classical centroid algorithm and more than 50% improvement was achieved.","PeriodicalId":37369,"journal":{"name":"International Journal of Optimization and Control: Theories and Applications","volume":"1965 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91301442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-14DOI: 10.11121/ijocta.2022.1208
Aadil Rashid Sheergojri, P. Iqbal, P. Agarwal, Necati Ozdemir
For treating cancer, tumor growth models have shown to be a valuable resource, whether they are used to develop therapeutic methods paired with process control or to simulate and evaluate treatment processes. In addition, a fuzzy mathematical model is a tool for monitoring the influences of various elements and creating behavioral assessments. It has been designed to decrease the ambiguity of model parameters to obtain a reliable mathematical tumor development model by employing fuzzy logic.The tumor Gompertz equation is shown in an imprecise environment in this study. It considers the whole cancer cell population to be vague at any given time, with the possibility distribution function determined by the initial tumor cell population, tumor net population rate, and carrying capacity of the tumor. Moreover, this work provides information on the expected tumor cell population in the maximum period. This study examines fuzzy tumor growth modeling insights based on fuzziness to reduce tumor uncertainty and achieve a degree of realism. Finally, numerical simulations are utilized to show the significant conclusions of the proposed study.
{"title":"Uncertainty-based Gompertz growth model for tumor population and its numerical analysis","authors":"Aadil Rashid Sheergojri, P. Iqbal, P. Agarwal, Necati Ozdemir","doi":"10.11121/ijocta.2022.1208","DOIUrl":"https://doi.org/10.11121/ijocta.2022.1208","url":null,"abstract":"For treating cancer, tumor growth models have shown to be a valuable resource, whether they are used to develop therapeutic methods paired with process control or to simulate and evaluate treatment processes. In addition, a fuzzy mathematical model is a tool for monitoring the influences of various elements and creating behavioral assessments. It has been designed to decrease the ambiguity of model parameters to obtain a reliable mathematical tumor development model by employing fuzzy logic.The tumor Gompertz equation is shown in an imprecise environment in this study. It considers the whole cancer cell population to be vague at any given time, with the possibility distribution function determined by the initial tumor cell population, tumor net population rate, and carrying capacity of the tumor. Moreover, this work provides information on the expected tumor cell population in the maximum period. This study examines fuzzy tumor growth modeling insights based on fuzziness to reduce tumor uncertainty and achieve a degree of realism. Finally, numerical simulations are utilized to show the significant conclusions of the proposed study.","PeriodicalId":37369,"journal":{"name":"International Journal of Optimization and Control: Theories and Applications","volume":"32 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78369071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-12DOI: 10.11121/ijocta.2022.1166
Vandana Kakran, J. Dhodiya
This paper focusses on the development of a Multi-choice Multi-objective Transportation Problem (MCMOTP) in the uncertain environment. The parameters associated with the objective functions in MCMOTP are regarded as uncertain variables and the other parameters associated with supply capacity and demand requirements are considered under the multi-choice environment. In this paper, two ranking criteria have been utilized to convert the uncertain objectives into their crisp form. Using these two ranking criteria for the uncertain MCMOTP model, two deterministic models have been developed namely, Expected Value Model (EV Model) and Optimistic Value Model (OV Model). The multi-choice parameters in the constraints are converted to a single choice parameters with the help of binary variable approach. The EV and OV models are solved directly in the LINGO 18.0 software using minimizing distance method and fuzzy programming technique. At last, a numerical illustration is provided to demonstrate the application and algorithm of the models. The sensitivity of the objective functions in OV Model is also examined with respect to the confidence levels to investigate variation in the objective functions.
{"title":"A belief-degree based multi-objective transportation problem with multi-choice demand and supply","authors":"Vandana Kakran, J. Dhodiya","doi":"10.11121/ijocta.2022.1166","DOIUrl":"https://doi.org/10.11121/ijocta.2022.1166","url":null,"abstract":"This paper focusses on the development of a Multi-choice Multi-objective Transportation Problem (MCMOTP) in the uncertain environment. The parameters associated with the objective functions in MCMOTP are regarded as uncertain variables and the other parameters associated with supply capacity and demand requirements are considered under the multi-choice environment. In this paper, two ranking criteria have been utilized to convert the uncertain objectives into their crisp form. Using these two ranking criteria for the uncertain MCMOTP model, two deterministic models have been developed namely, Expected Value Model (EV Model) and Optimistic Value Model (OV Model). The multi-choice parameters in the constraints are converted to a single choice parameters with the help of binary variable approach. The EV and OV models are solved directly in the LINGO 18.0 software using minimizing distance method and fuzzy programming technique. At last, a numerical illustration is provided to demonstrate the application and algorithm of the models. The sensitivity of the objective functions in OV Model is also examined with respect to the confidence levels to investigate variation in the objective functions.","PeriodicalId":37369,"journal":{"name":"International Journal of Optimization and Control: Theories and Applications","volume":"72 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87984705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-12DOI: 10.11121/ijocta.2022.1227
Esma Canhasi Kasemi
Data Envelopment Analysis (DEA) evaluates a large number of input and output variables using mathematical programming techniques and analyzes the effectiveness of similar decision making units (DMU). Unlike traditional methods, the most important advantage of DEA is that the weights of input and output variables can be defined by the analyzer. In this study, the limitations of the DEA weights were determined using the AHP, which considers expert opinion. In addition, an alternative judgment scale was used for the Saaty judgment scale, which is used as a standard in the AHP method, and thus a more sensitive analysis was performed. There have been studies dealing with the comparison of judgment scales, but few studies on consistency sensitivity are needed. This point has also been addressed in this study. Subsequently, the financial efficiency of 27 companies operating in the food sector in Kosovo was evaluated with the weight-restricted DEA model, first created using the unweighted DEA model and then the AHP model, and the two models were compared. This paper is the first one of its kind since there are no previous studies regarding the examination of the financial efficiency of companies operating in the Kosovo food sector based on the DEAHP method.
{"title":"Financial efficiency of companies operating in the Kosovo food sector: DEA and DEAHP","authors":"Esma Canhasi Kasemi","doi":"10.11121/ijocta.2022.1227","DOIUrl":"https://doi.org/10.11121/ijocta.2022.1227","url":null,"abstract":"Data Envelopment Analysis (DEA) evaluates a large number of input and output variables using mathematical programming techniques and analyzes the effectiveness of similar decision making units (DMU). Unlike traditional methods, the most important advantage of DEA is that the weights of input and output variables can be defined by the analyzer. In this study, the limitations of the DEA weights were determined using the AHP, which considers expert opinion. In addition, an alternative judgment scale was used for the Saaty judgment scale, which is used as a standard in the AHP method, and thus a more sensitive analysis was performed. There have been studies dealing with the comparison of judgment scales, but few studies on consistency sensitivity are needed. This point has also been addressed in this study. Subsequently, the financial efficiency of 27 companies operating in the food sector in Kosovo was evaluated with the weight-restricted DEA model, first created using the unweighted DEA model and then the AHP model, and the two models were compared. This paper is the first one of its kind since there are no previous studies regarding the examination of the financial efficiency of companies operating in the Kosovo food sector based on the DEAHP method.","PeriodicalId":37369,"journal":{"name":"International Journal of Optimization and Control: Theories and Applications","volume":"30 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79196168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-12DOI: 10.11121/ijocta.2022.1161
Yasin Göçgün, N. O. Bakır
Sports scheduling problems are interesting optimization problems that require the decision of who play with whom, where and when to play. In this work, we study the sports scheduling problem faced by the Turkish Football Federation. Given the schedule of games for each round of the season, the problem is to determine the match days with the goal of having a fair schedule for each team. The criteria we employ to establish this fairness are achieving an equal distribution of match days between the teams throughout the season and the ideal assignment of games to different days in each round of the tournament. The problem is formulated as a nonlinear binary integer program and is solved optimally for each week. Our results indicate that significant improvements over the existing schedule can be achieved if the optimal solution is implemented.
{"title":"Optimal matchday schedule for Turkish professional soccer league using nonlinear binary integer programming","authors":"Yasin Göçgün, N. O. Bakır","doi":"10.11121/ijocta.2022.1161","DOIUrl":"https://doi.org/10.11121/ijocta.2022.1161","url":null,"abstract":"Sports scheduling problems are interesting optimization problems that require the decision of who play with whom, where and when to play. In this work, we study the sports scheduling problem faced by the Turkish Football Federation. Given the schedule of games for each round of the season, the problem is to determine the match days with the goal of having a fair schedule for each team. The criteria we employ to establish this fairness are achieving an equal distribution of match days between the teams throughout the season and the ideal assignment of games to different days in each round of the tournament. The problem is formulated as a nonlinear binary integer program and is solved optimally for each week. Our results indicate that significant improvements over the existing schedule can be achieved if the optimal solution is implemented.","PeriodicalId":37369,"journal":{"name":"International Journal of Optimization and Control: Theories and Applications","volume":"1 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85988459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-13DOI: 10.11121/ijocta.2022.1181
A. D. Karaoglan, Deniz Perin
The aim of this study is to calculate the optimum factor levels for the design parameters namely slot pitch, center slot pitch, and damper width to keep the magnetic flux density distribution in a desired range while minimizing the total harmonic distortion (THD). For this purpose, the numerical simulations are performed in the Maxwell environment. Then by the aid of regression modeling over this simulation results; the mathematical equations between the responses (THD and magnetic flux density distribution) and the factors are calculated. After the modeling phase, grasshopper optimization algorithm (GOA) is run through these regression equations to determine the optimum values of the rotor design parameters (factors). The confirmations are also performed in the Maxwell environment and the result indicated that the THD is minimized and the magnetic flux density distribution on the teeth is kept in a desired range.
{"title":"Rotor design optimization of a synchronous generator by considering the damper winding effect to minimize THD using grasshopper optimization algorithm","authors":"A. D. Karaoglan, Deniz Perin","doi":"10.11121/ijocta.2022.1181","DOIUrl":"https://doi.org/10.11121/ijocta.2022.1181","url":null,"abstract":"The aim of this study is to calculate the optimum factor levels for the design parameters namely slot pitch, center slot pitch, and damper width to keep the magnetic flux density distribution in a desired range while minimizing the total harmonic distortion (THD). For this purpose, the numerical simulations are performed in the Maxwell environment. Then by the aid of regression modeling over this simulation results; the mathematical equations between the responses (THD and magnetic flux density distribution) and the factors are calculated. After the modeling phase, grasshopper optimization algorithm (GOA) is run through these regression equations to determine the optimum values of the rotor design parameters (factors). The confirmations are also performed in the Maxwell environment and the result indicated that the THD is minimized and the magnetic flux density distribution on the teeth is kept in a desired range.","PeriodicalId":37369,"journal":{"name":"International Journal of Optimization and Control: Theories and Applications","volume":"63 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77156080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-12DOI: 10.11121/ijocta.2022.1158
Alperen Ekrem Çelikdin
In the feed sector, 95% of the input costs arise from the supply of raw materials used in feed production. The selling price is determined by competition in free market conditions. Due to the use of similar technologies and the very small share of production costs in total costs, it is unlikely that a competitive advantage will be gained through innovations in production. Between 30% and 50% of grain products are used in feed ration analysis. Cereals can only be harvested at a certain time of the year. Due to this limited time frame, feed production enterprises have to balance their financial burdens with their operational needs while making their annual stocks. The study was carried out to cover all the relevant businesses of the company, which has feed factories in four regions of Turkey. Based on the season data of the year 2020-2021, the grain purchase planning for the year 2021-2022 was tried to be optimized with non-linear programming. While creating the mathematical model, grain prices, interest rates, production needs according to production planning, sales according to sales forecasts, factory stocking capacities, licensed warehouse rental, transportation, handling and transshipment costs were taken into account. With this unique paper, in the cattle feed production sector, storage, transportation and handling costs will be minimized. Cost advantage will be provided with optimum purchase planning in the season. According to the grain pricing forecast and market data for the 2021-2022 season, model can provide a cost advantage of 0.7%. Model will also provide insight to the managers for additional storage space investments.
{"title":"Optimizing seasonal grain intakes with non-linear programming: An application in the feed industry","authors":"Alperen Ekrem Çelikdin","doi":"10.11121/ijocta.2022.1158","DOIUrl":"https://doi.org/10.11121/ijocta.2022.1158","url":null,"abstract":"In the feed sector, 95% of the input costs arise from the supply of raw materials used in feed production. The selling price is determined by competition in free market conditions. Due to the use of similar technologies and the very small share of production costs in total costs, it is unlikely that a competitive advantage will be gained through innovations in production. Between 30% and 50% of grain products are used in feed ration analysis. Cereals can only be harvested at a certain time of the year. Due to this limited time frame, feed production enterprises have to balance their financial burdens with their operational needs while making their annual stocks. The study was carried out to cover all the relevant businesses of the company, which has feed factories in four regions of Turkey. Based on the season data of the year 2020-2021, the grain purchase planning for the year 2021-2022 was tried to be optimized with non-linear programming. While creating the mathematical model, grain prices, interest rates, production needs according to production planning, sales according to sales forecasts, factory stocking capacities, licensed warehouse rental, transportation, handling and transshipment costs were taken into account.\u0000With this unique paper, in the cattle feed production sector, storage, transportation and handling costs will be minimized. Cost advantage will be provided with optimum purchase planning in the season. According to the grain pricing forecast and market data for the 2021-2022 season, model can provide a cost advantage of 0.7%. Model will also provide insight to the managers for additional storage space investments.","PeriodicalId":37369,"journal":{"name":"International Journal of Optimization and Control: Theories and Applications","volume":"83 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84762224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-02DOI: 10.11121/ijocta.2022.1137
Akshay Joshi
The flexo process parameters play an important role in ink transfer and will lead to wastage of inks, substrate, solvents and printed stocks if not monitored and controlled. The work focuses on optimizing the flexo process parameters for 40 microns 3-layer polyethylene (PE) film with Blue Nitrocellulose (NC) ink to reduce overall manufacturing cost while maintaining the print quality for diaper application. An experimental design was conducted for the response Ink GSM (grams per square meter), ?E and Print Mottle with factors such as ink viscosity, anilox volume, plate dot shape and substrate opacity. The data was analyzed through Main Effect, Interaction Plot and Analysis of Variance (ANOVA). The regression models were developed for the response to validate the predictive ability of model. The process optimization resulted in reduction of Ink GSM, ?E and Print Mottle by 18%, 52% and 1% respectively. The ink consumption reduced by 18.26% with minimized print defects, thereby reducing the overall manufacturing cost.
{"title":"Optimization of flexo process parameters to reduce the overall manufacturing cost","authors":"Akshay Joshi","doi":"10.11121/ijocta.2022.1137","DOIUrl":"https://doi.org/10.11121/ijocta.2022.1137","url":null,"abstract":"The flexo process parameters play an important role in ink transfer and will lead to wastage of inks, substrate, solvents and printed stocks if not monitored and controlled. The work focuses on optimizing the flexo process parameters for 40 microns 3-layer polyethylene (PE) film with Blue Nitrocellulose (NC) ink to reduce overall manufacturing cost while maintaining the print quality for diaper application. An experimental design was conducted for the response Ink GSM (grams per square meter), ?E and Print Mottle with factors such as ink viscosity, anilox volume, plate dot shape and substrate opacity. The data was analyzed through Main Effect, Interaction Plot and Analysis of Variance (ANOVA). The regression models were developed for the response to validate the predictive ability of model. The process optimization resulted in reduction of Ink GSM, ?E and Print Mottle by 18%, 52% and 1% respectively. The ink consumption reduced by 18.26% with minimized print defects, thereby reducing the overall manufacturing cost.","PeriodicalId":37369,"journal":{"name":"International Journal of Optimization and Control: Theories and Applications","volume":"10 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84180850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-02DOI: 10.11121/ijocta.2022.1025
M. Kumari, P. K. De
This paper presents an EOQ model where demand is dependent upon time and selling price. In the proposed model of inventory, the retailer allows its unsatisfied customers to return their product whereas the manufacturer offers a full trade credit policy to the retailer. To make our model realistic, we have assumed that the product returned can be resold with the same selling price. Number of returns is a function of demand. In this proposed inventory model considering deterioration, the retailer does not fully reimburse its customers for the returned product. The primary purpose of this inventory model is to determine the optimal selling price, optimal order quantity, and optimal replenishment cycle length in order to maximize the retailer’s total profit earned per unit time. A numerical example is also presented and a sensitivity analysis is carried to highlight the findings of the suggested inventory model.
{"title":"An EOQ model for deteriorating items analyzing retailer’s optimal strategy under trade credit and return policy with nonlinear demand and resalable returns","authors":"M. Kumari, P. K. De","doi":"10.11121/ijocta.2022.1025","DOIUrl":"https://doi.org/10.11121/ijocta.2022.1025","url":null,"abstract":"This paper presents an EOQ model where demand is dependent upon time and selling price. In the proposed model of inventory, the retailer allows its unsatisfied customers to return their product whereas the manufacturer offers a full trade credit policy to the retailer. To make our model realistic, we have assumed that the product returned can be resold with the same selling price. Number of returns is a function of demand. In this proposed inventory model considering deterioration, the retailer does not fully reimburse its customers for the returned product. The primary purpose of this inventory model is to determine the optimal selling price, optimal order quantity, and optimal replenishment cycle length in order to maximize the retailer’s total profit earned per unit time. A numerical example is also presented and a sensitivity analysis is carried to highlight the findings of the suggested inventory model.","PeriodicalId":37369,"journal":{"name":"International Journal of Optimization and Control: Theories and Applications","volume":"17 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86687297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.11121/ijocta.2022.1084
Ayse Ozmen
Residential customers are the main users generally need a great quantity of natural gas in distribution systems, especially, in the wintry weather season since it is particularly consumed for cooking and space heating. Hence, it ought to be non-interruptible. Since distribution systems have a restricted ability for supply, reasonable planning and prediction through the whole year, especially in winter seasons, have emerged as vital. The Ridge Regression (RR) is formulated mainly to decrease collinearity results through shrinking the regression coefficients and reducing the impact in the model of variables. Conic multivariate adaptive regression splines ((C)MARS) model is constructed as an effective choice for MARS by using inverse problems, statistical learning, and multi-objective optimization theories. In this approach, the model complexity is penalized in the structure of RR and it is constructed a relaxation by utilizing continuous optimization, called Conic Quadratic Programming (CQP). In this study, CMARS and RR are applied to obtain forecasts of residential natural gas demand for local distribution companies (LDCs) that require short-term forecasts, and the model performances are compared by using some criteria. Here, our analysis shows that CMARS models outperform RR models. For one-day-ahead forecasts, CMARS yields a MAPE of about 4.8%, while the same value under RR reaches 8.5%. As the forecast horizon increases, it can be seen that the performance of the methods becomes worse, and for a forecast one week ahead, the MAPE values for CMARS and RR are 9.9% and 18.3%, respectively.
{"title":"Multi-objective regression modeling for natural gas prediction with ridge regression and CMARS","authors":"Ayse Ozmen","doi":"10.11121/ijocta.2022.1084","DOIUrl":"https://doi.org/10.11121/ijocta.2022.1084","url":null,"abstract":"Residential customers are the main users generally need a great quantity of natural gas in distribution systems, especially, in the wintry weather season since it is particularly consumed for cooking and space heating. Hence, it ought to be non-interruptible. Since distribution systems have a restricted ability for supply, reasonable planning and prediction through the whole year, especially in winter seasons, have emerged as vital. The Ridge Regression (RR) is formulated mainly to decrease collinearity results through shrinking the regression coefficients and reducing the impact in the model of variables. Conic multivariate adaptive regression splines ((C)MARS) model is constructed as an effective choice for MARS by using inverse problems, statistical learning, and multi-objective optimization theories. In this approach, the model complexity is penalized in the structure of RR and it is constructed a relaxation by utilizing continuous optimization, called Conic Quadratic Programming (CQP). In this study, CMARS and RR are applied to obtain forecasts of residential natural gas demand for local distribution companies (LDCs) that require short-term forecasts, and the model performances are compared by using some criteria. Here, our analysis shows that CMARS models outperform RR models. For one-day-ahead forecasts, CMARS yields a MAPE of about 4.8%, while the same value under RR reaches 8.5%. As the forecast horizon increases, it can be seen that the performance of the methods becomes worse, and for a forecast one week ahead, the MAPE values for CMARS and RR are 9.9% and 18.3%, respectively.","PeriodicalId":37369,"journal":{"name":"International Journal of Optimization and Control: Theories and Applications","volume":"30 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79011857","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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