Systems Engineering (SE) is a new engineering method for many firms in Automotive Product Development that expectedly advances their development processes to meet their stakeholder needs more effectively. Literature suggest that understanding and acceptance are key factors in the implementation, however comprehensive modes for their increase are barely discussed. In this paper, we propose a Participatory Action Research based on multiple research elements to find an effective technique for gaining understanding and acceptance on SE in a validated model environment of automotive industry called Formula SAE. We present practical outcomes at each steps of the implementation process and analyze the effect of improvements in the context of strategy, structure processes.
{"title":"Understanding and acceptance of systems engineering in automotive product development","authors":"Tamás Kolossváry, D. Feszty, B. Filep, T. Dőry","doi":"10.31181/dmame04012023k","DOIUrl":"https://doi.org/10.31181/dmame04012023k","url":null,"abstract":"Systems Engineering (SE) is a new engineering method for many firms in Automotive Product Development that expectedly advances their development processes to meet their stakeholder needs more effectively. Literature suggest that understanding and acceptance are key factors in the implementation, however comprehensive modes for their increase are barely discussed. In this paper, we propose a Participatory Action Research based on multiple research elements to find an effective technique for gaining understanding and acceptance on SE in a validated model environment of automotive industry called Formula SAE. We present practical outcomes at each steps of the implementation process and analyze the effect of improvements in the context of strategy, structure processes.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69623424","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}
Mohammad Khodashenas, S. Najafi, H. Kazemipoor, Movahedi Sobhani
This paper modeled and solved an integrated multi-depot vehicle routing problem (MDVRP) with simultaneous pickup and delivery (SPD) with package layout under unpredictable pickup, delivery, and transfer costs. The model described in this paper is divided into two stages. In the first stage, the SCA algorithm is used to optimize the package dimensions (a collection of commodities consumers need). The NSGA II and MOALO algorithms are used in the second stage to optimize the three objective functions of 1 simultaneously) minimizing total costs, 2) minimizing co2 emissions, and 3) minimizing the maximum working hours of drivers based on the optimal dimensions (length, width, and height) obtained from solving the first stage model. Determining the quantity and ideal location of possible warehouses, the best route for trucks to take to deliver and collect customer items, and the distribution of customers to warehouses are the key goals of the second stage. Since the model is unclear, the problem's uncertainty parameters are controlled using a novel fuzzy-robust box optimization (FRBO) technique. This technique, which combines the advantages of fuzzy programming with robust box-based optimization, produces excellent results when used to optimize objective functions. The numerical calculations in the numerical example show that the total network costs and CO2 emissions increased in the second stage in the presented model with an increasing uncertainty rate. At the same time, the maximum working hours of drivers decreased due to the shortened communication route and the number of vehicles increasing. Finally, the MOALO algorithm was used to resolve a case study at Safir Broadcasting Company because of its excellent efficiency in resolving the created model, the findings of which revealed the presence of 13 potential effective solutions. The quantity of greenhouse gas emissions rose by 1.11%, the overall expenditures climbed by 1.72%, and the number of hours that drivers worked fell by 11.98% when the uncertainty rate was raised from 0.5 to 0.7, according to research on the FRBO.
{"title":"Providing an integrated multi-depot vehicle routing problem model with simultaneous pickup and delivery and package layout under uncertainty with fuzzy-robust box optimization method","authors":"Mohammad Khodashenas, S. Najafi, H. Kazemipoor, Movahedi Sobhani","doi":"10.31181/dmame622023640","DOIUrl":"https://doi.org/10.31181/dmame622023640","url":null,"abstract":"This paper modeled and solved an integrated multi-depot vehicle routing problem (MDVRP) with simultaneous pickup and delivery (SPD) with package layout under unpredictable pickup, delivery, and transfer costs. The model described in this paper is divided into two stages. In the first stage, the SCA algorithm is used to optimize the package dimensions (a collection of commodities consumers need). The NSGA II and MOALO algorithms are used in the second stage to optimize the three objective functions of 1 simultaneously) minimizing total costs, 2) minimizing co2 emissions, and 3) minimizing the maximum working hours of drivers based on the optimal dimensions (length, width, and height) obtained from solving the first stage model. Determining the quantity and ideal location of possible warehouses, the best route for trucks to take to deliver and collect customer items, and the distribution of customers to warehouses are the key goals of the second stage. Since the model is unclear, the problem's uncertainty parameters are controlled using a novel fuzzy-robust box optimization (FRBO) technique. This technique, which combines the advantages of fuzzy programming with robust box-based optimization, produces excellent results when used to optimize objective functions. The numerical calculations in the numerical example show that the total network costs and CO2 emissions increased in the second stage in the presented model with an increasing uncertainty rate. At the same time, the maximum working hours of drivers decreased due to the shortened communication route and the number of vehicles increasing. Finally, the MOALO algorithm was used to resolve a case study at Safir Broadcasting Company because of its excellent efficiency in resolving the created model, the findings of which revealed the presence of 13 potential effective solutions. The quantity of greenhouse gas emissions rose by 1.11%, the overall expenditures climbed by 1.72%, and the number of hours that drivers worked fell by 11.98% when the uncertainty rate was raised from 0.5 to 0.7, according to research on the FRBO.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69623232","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 : 2023-01-01DOI: 10.31181/dmame0601051229022s
Saloua Said, Hafida Bouloiz, M. Gallab
The present paper came into existence with the specific purpose of providing an optimized process that enables making resilient decisions in an uncertain context, and here our interest is particularly focused on the activity of new venture creation and on the entrepreneurial decision-making logic, in particular, effectuation theory. Within this framework, the rational resilience-based decision-making model (R2DM) is introduced. The relevant steps of this model are: (1) The identification of the problem and the available options. In this instance, the studied situation is the effectual customer co-creation case, and the available alternatives are planning, visionary, adaptative and transforming approaches, (2) The definition of the selection criteria that should be used to evaluate the available alternatives. In our case, these criteria are the six principles of entrepreneurial resilience, which are set out in detail, (3) The choice of the methodology to be followed in assessing the available options. To that end, three interconnected methods, based mainly on logical thinking and reasoning, are proposed. They are respectively devoted to Entrepreneurial resilience (ER) calculation, options classification using logistic regression algorithm, and the determination of the most resilient route to reach objectives employing graph theory. The obtained results are compared to what is advocated in the literature and conclusions are made.
{"title":"New model for making resilient decisions in an uncertain context: The rational resilience-based decision-making model (R2DM)","authors":"Saloua Said, Hafida Bouloiz, M. Gallab","doi":"10.31181/dmame0601051229022s","DOIUrl":"https://doi.org/10.31181/dmame0601051229022s","url":null,"abstract":"The present paper came into existence with the specific purpose of providing an optimized process that enables making resilient decisions in an uncertain context, and here our interest is particularly focused on the activity of new venture creation and on the entrepreneurial decision-making logic, in particular, effectuation theory. Within this framework, the rational resilience-based decision-making model (R2DM) is introduced. The relevant steps of this model are: (1) The identification of the problem and the available options. In this instance, the studied situation is the effectual customer co-creation case, and the available alternatives are planning, visionary, adaptative and transforming approaches, (2) The definition of the selection criteria that should be used to evaluate the available alternatives. In our case, these criteria are the six principles of entrepreneurial resilience, which are set out in detail, (3) The choice of the methodology to be followed in assessing the available options. To that end, three interconnected methods, based mainly on logical thinking and reasoning, are proposed. They are respectively devoted to Entrepreneurial resilience (ER) calculation, options classification using logistic regression algorithm, and the determination of the most resilient route to reach objectives employing graph theory. The obtained results are compared to what is advocated in the literature and conclusions are made.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69623437","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 traditional scheduling, job processing times are assumed to be fixed. However, this assumption may not be applicable in many realistic industrial processes. Using the job processing time of real industrial processes instead of a fixed value converts the deterministic model to a stochastic one. This study provides three approaches to solving the problem of stochastic scheduling: stochastic linguistic, stochastic scenarios, and stochastic probabilistic. A combinatorial algorithm, dispatching rules and community evaluation chromosomes (DRCEC) is developed to generate an optimal sequence to minimize the tardiness performance measure in the scheduling problem. Thirty-five datasets of scheduling problems are generated and tested with the model. The DRCEC is compared to the Genetic Algorithm (GA) in terms of total tardiness, the tendency of convergence, execution time, and accuracy. The DRCEC has been discovered to outperform the GA. The computational results show that the DRCEC approach gives the optimal response in 63 per cent of cases and the near-optimal solution in the remaining 37 per cent of cases. Finally, a manufacturing company case study demonstrates DRCEC's acceptable performance.
{"title":"Optimal job scheduling to minimize total tardiness by dispatching rules and community evaluation chromosomes","authors":"Prasad Bari, P. Karande","doi":"10.31181/dmame622023700","DOIUrl":"https://doi.org/10.31181/dmame622023700","url":null,"abstract":"In traditional scheduling, job processing times are assumed to be fixed. However, this assumption may not be applicable in many realistic industrial processes. Using the job processing time of real industrial processes instead of a fixed value converts the deterministic model to a stochastic one. This study provides three approaches to solving the problem of stochastic scheduling: stochastic linguistic, stochastic scenarios, and stochastic probabilistic. A combinatorial algorithm, dispatching rules and community evaluation chromosomes (DRCEC) is developed to generate an optimal sequence to minimize the tardiness performance measure in the scheduling problem. Thirty-five datasets of scheduling problems are generated and tested with the model. The DRCEC is compared to the Genetic Algorithm (GA) in terms of total tardiness, the tendency of convergence, execution time, and accuracy. The DRCEC has been discovered to outperform the GA. The computational results show that the DRCEC approach gives the optimal response in 63 per cent of cases and the near-optimal solution in the remaining 37 per cent of cases. Finally, a manufacturing company case study demonstrates DRCEC's acceptable performance.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69623461","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 study examines the risk behaviour of a decision-maker regarding pricing decisions with the aid of the newsvendor model. In this regard, prospect theory and reference point concept are adopted to formulate the value function of the decision-maker. Unlike the traditional reference points (quantity-based), a reference point is deemed a function of the price. It is proved that a convex combination of the maximum-expected profits and expected losses represents the reference point. Closed-form solutions for the optimum price and quantity orders are obtained under uniformly and exponentially distributed demand. Moreover, the risk when the ordering quantity does not match the actual demand is discussed. The results-based numerical experiments reveal that the risk-averse decision-maker manages to increase the price to evade different expected costs, such as shortages and overstocking. Finally, for the same risk aversion level, the maximum reduction percentage of the optimal quantity concerning the price reaches approximately 8% in the exponential distribution, whereas it decreases by approximately 30% under the uniform distribution.
{"title":"Risk-averse pricing decisions based on prospect theory","authors":"I. Shaban","doi":"10.31181/dmame622023629","DOIUrl":"https://doi.org/10.31181/dmame622023629","url":null,"abstract":"This study examines the risk behaviour of a decision-maker regarding pricing decisions with the aid of the newsvendor model. In this regard, prospect theory and reference point concept are adopted to formulate the value function of the decision-maker. Unlike the traditional reference points (quantity-based), a reference point is deemed a function of the price. It is proved that a convex combination of the maximum-expected profits and expected losses represents the reference point. Closed-form solutions for the optimum price and quantity orders are obtained under uniformly and exponentially distributed demand. Moreover, the risk when the ordering quantity does not match the actual demand is discussed. The results-based numerical experiments reveal that the risk-averse decision-maker manages to increase the price to evade different expected costs, such as shortages and overstocking. Finally, for the same risk aversion level, the maximum reduction percentage of the optimal quantity concerning the price reaches approximately 8% in the exponential distribution, whereas it decreases by approximately 30% under the uniform distribution.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69623678","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}
S. M. Moosavi, M. Seifbarghy, Seyed Mohamad Haji Molana
This study models a closed loop supply chain network for the Iranian engine oil market. The primary goal of the created model is to summarize tactical choices like choosing the best degree of discount and allocating the best flow of products across facilities as well as strategic decisions like selecting a supplier and finding new facilities. The three aim functions of reducing overall expenses, optimizing employment rate, and limiting unrealized demand are considered. The novel flexible fuzzy robust optimization approach also controls the uncertainty parameters and the meta-heuristics algorithm for solving the model. This investigation showed that the network's overall transportation and operational expenses have risen as the rate of uncertainty and dependability has grown. MOGWO was chosen as an effective algorithm and employed in solving numerical examples of more significant size after the final examination of comparison indices between solution techniques (case study). According to the findings of a case study, the four oil businesses, Behran, Sepahan, Iranol, and Pars, were chosen as the best production hubs since they can generate 514 million liters of engine oil annually. As a consequence, building the network cost a total of 434321010 million Rials, required the employment of more than 37 thousand individuals, and left 90 million liters of fuel short.
{"title":"Flexible fuzzy-robust optimization method in closed-loop supply chain network problem modeling for the engine oil industry","authors":"S. M. Moosavi, M. Seifbarghy, Seyed Mohamad Haji Molana","doi":"10.31181/dmame622023569","DOIUrl":"https://doi.org/10.31181/dmame622023569","url":null,"abstract":"This study models a closed loop supply chain network for the Iranian engine oil market. The primary goal of the created model is to summarize tactical choices like choosing the best degree of discount and allocating the best flow of products across facilities as well as strategic decisions like selecting a supplier and finding new facilities. The three aim functions of reducing overall expenses, optimizing employment rate, and limiting unrealized demand are considered. The novel flexible fuzzy robust optimization approach also controls the uncertainty parameters and the meta-heuristics algorithm for solving the model. This investigation showed that the network's overall transportation and operational expenses have risen as the rate of uncertainty and dependability has grown. MOGWO was chosen as an effective algorithm and employed in solving numerical examples of more significant size after the final examination of comparison indices between solution techniques (case study). According to the findings of a case study, the four oil businesses, Behran, Sepahan, Iranol, and Pars, were chosen as the best production hubs since they can generate 514 million liters of engine oil annually. As a consequence, building the network cost a total of 434321010 million Rials, required the employment of more than 37 thousand individuals, and left 90 million liters of fuel short.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69623539","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 study examines the robust facility layout problem (RFLP) while taking into account unpredictable health and environmental safety standards. This problem's major goal is to arrange the departments in various departments of a hall, allot each department the appropriate amount of space, and identify the kind of amenities and equipment needed for each chosen sector. To accomplish the aforementioned objective, five criteria were taken into account: the total cost of department transfer and selection; access to more facilities and equipment; access to firefighting equipment; access to favorable climatic conditions; and the separation of noisy departments from one another. The fuzzy programming approach is utilized in this research to regulate the uncertainty parameters due to the uncertainty of the transfer cost and transfer time parameters. Additionally, by supplying an appropriate chromosome, the precise Epsilon constraint approach, NSGA II, and MOPSO have been employed to tackle the issue. The computational sizes of larger-sized sample problems solved demonstrate the strong performance of the NSGA II in quickly finding effective solutions.
{"title":"Modeling the robust facility layout problem for unequal space considering health and environmental safety criteria under uncertain parameters","authors":"A. Ghaseminejad, H. Kazemipoor, M. Fallah","doi":"10.31181/dmame622023607","DOIUrl":"https://doi.org/10.31181/dmame622023607","url":null,"abstract":"This study examines the robust facility layout problem (RFLP) while taking into account unpredictable health and environmental safety standards. This problem's major goal is to arrange the departments in various departments of a hall, allot each department the appropriate amount of space, and identify the kind of amenities and equipment needed for each chosen sector. To accomplish the aforementioned objective, five criteria were taken into account: the total cost of department transfer and selection; access to more facilities and equipment; access to firefighting equipment; access to favorable climatic conditions; and the separation of noisy departments from one another. The fuzzy programming approach is utilized in this research to regulate the uncertainty parameters due to the uncertainty of the transfer cost and transfer time parameters. Additionally, by supplying an appropriate chromosome, the precise Epsilon constraint approach, NSGA II, and MOPSO have been employed to tackle the issue. The computational sizes of larger-sized sample problems solved demonstrate the strong performance of the NSGA II in quickly finding effective solutions.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69623583","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}
To investigate the influence of E-Leadership on organizational innovation performance (OIP), data from previous studies were analyzed, and a theoretical model containing E-Leadership, employee innovation behavior (EIB), followership, and OIP was constructed using the theoretical frameworks of the Supervisor's Organizational Embodiment (SOE) theory, social learning theory, and "social man" hypothesis. Subsequently, to investigate the interrelationships of E-Leadership, followership, and OIP, 372 questionnaire responses were collected from workers at representative Chinese foreign export enterprises, and data were analyzed using a manager–employee-matched design. Data analysis showed that: (1) The six dimensions of E-Leadership have a positive impact on OIP, (2) EIB mediates the effect of the six E-Leadership dimensions on OIP, and (3) The effects of E-Communication, E-Change, and E-Tech on EIB are negatively moderated by followership. Therefore, the findings suggest that organizations can improve innovation performance by improving managers' E-Leadership. At the same time, they should effectively influence employees' followership to prevent reductions in innovation behavior due to over-compliance with managers. This study not only provides a reference for enterprises to improve their OIP but also promotes theoretical research on E-Leadership.
{"title":"Impact of e-leadership on organizational innovation performance: Role of employee followership","authors":"L. Zhong, Rerkchai Fooprateepsiri, Ruihui Pu","doi":"10.31181/dmame622023728","DOIUrl":"https://doi.org/10.31181/dmame622023728","url":null,"abstract":"To investigate the influence of E-Leadership on organizational innovation performance (OIP), data from previous studies were analyzed, and a theoretical model containing E-Leadership, employee innovation behavior (EIB), followership, and OIP was constructed using the theoretical frameworks of the Supervisor's Organizational Embodiment (SOE) theory, social learning theory, and \"social man\" hypothesis. Subsequently, to investigate the interrelationships of E-Leadership, followership, and OIP, 372 questionnaire responses were collected from workers at representative Chinese foreign export enterprises, and data were analyzed using a manager–employee-matched design. Data analysis showed that: (1) The six dimensions of E-Leadership have a positive impact on OIP, (2) EIB mediates the effect of the six E-Leadership dimensions on OIP, and (3) The effects of E-Communication, E-Change, and E-Tech on EIB are negatively moderated by followership. Therefore, the findings suggest that organizations can improve innovation performance by improving managers' E-Leadership. At the same time, they should effectively influence employees' followership to prevent reductions in innovation behavior due to over-compliance with managers. This study not only provides a reference for enterprises to improve their OIP but also promotes theoretical research on E-Leadership.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69624037","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}
F. Ramos, M. T. Pereira, Marisa Oliveira, Lihki Rubio
A good command of computational and statistical tools has proven advantageous when modelling and forecasting time series. According to recent literature, neural networks with long memory (e.g., Short-Term Long Memory) are a promising option in deep learning methods. However, only some works also consider the computational cost of these architectures compared to simpler architectures (e.g., Multilayer Perceptron). This work aims to provide insight into the memory performance of some Deep Neural Network architectures and their computational complexity. Another goal is to evaluate whether choosing more complex architectures with higher computational costs is justified. Error metrics are then used to assess the forecasting models' performance and computational cost. Two-time series related to e-commerce retail sales in the US were selected: (i) sales volume; (ii) e-commerce sales as a percentage of total sales. Although there are changes in data dynamics in both series, other existing characteristics lead to different conclusions. "Long memory" allows for significantly better forecasts in one-time series. In the other time series, this is not the case.
{"title":"The memory concept behind deep neural network models: An application in time series forecasting in the e-Commerce sector","authors":"F. Ramos, M. T. Pereira, Marisa Oliveira, Lihki Rubio","doi":"10.31181/dmame622023695","DOIUrl":"https://doi.org/10.31181/dmame622023695","url":null,"abstract":"A good command of computational and statistical tools has proven advantageous when modelling and forecasting time series. According to recent literature, neural networks with long memory (e.g., Short-Term Long Memory) are a promising option in deep learning methods. However, only some works also consider the computational cost of these architectures compared to simpler architectures (e.g., Multilayer Perceptron). This work aims to provide insight into the memory performance of some Deep Neural Network architectures and their computational complexity. Another goal is to evaluate whether choosing more complex architectures with higher computational costs is justified. Error metrics are then used to assess the forecasting models' performance and computational cost. Two-time series related to e-commerce retail sales in the US were selected: (i) sales volume; (ii) e-commerce sales as a percentage of total sales. Although there are changes in data dynamics in both series, other existing characteristics lead to different conclusions. \"Long memory\" allows for significantly better forecasts in one-time series. In the other time series, this is not the case.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69623393","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. Bazargan, S. E. Najafi, F. Lotfi, M. Fallah, Seyyed Ahmad Edalatpanah
Organizational performance evaluation is a crucial factor in making strategic decisions for the future. To plan for economic growth, it is important to measure the efficiency and productivity of organizations. Efficiency is a key indicator for evaluating the optimal performance of economic units. Petrochemical companies are vital components of a country's economy and their operations contribute to the growth and progress of different sectors. In countries where the economy relies heavily on this industry, such as ours, petroleum is of utmost importance. Data Envelopment Analysis is a widely used method for measuring productivity. This study aims to analyze the performance evaluation relates to the supply chain of petrochemical companies using the network DEA and Malmquist index. Efficiency and performance indices are calculated for each stage of the process. The study determines the indices through literature review, expert consultation, analysis, and visits to petrochemical companies. The input- and output-oriented multiplier models are used to assess overall and stage efficiencies. Using the efficiency values, the Malmquist productivity index is determined. The study examines unit productivity for the years 1395 to 1398, and the results indicate that most of the units experienced productivity growth during this period.
{"title":"Presenting a productivity analysis model for Iran oil industries using Malmquist network analysis","authors":"A. Bazargan, S. E. Najafi, F. Lotfi, M. Fallah, Seyyed Ahmad Edalatpanah","doi":"10.31181/dmame622023705","DOIUrl":"https://doi.org/10.31181/dmame622023705","url":null,"abstract":"Organizational performance evaluation is a crucial factor in making strategic decisions for the future. To plan for economic growth, it is important to measure the efficiency and productivity of organizations. Efficiency is a key indicator for evaluating the optimal performance of economic units. Petrochemical companies are vital components of a country's economy and their operations contribute to the growth and progress of different sectors. In countries where the economy relies heavily on this industry, such as ours, petroleum is of utmost importance. Data Envelopment Analysis is a widely used method for measuring productivity. This study aims to analyze the performance evaluation relates to the supply chain of petrochemical companies using the network DEA and Malmquist index. Efficiency and performance indices are calculated for each stage of the process. The study determines the indices through literature review, expert consultation, analysis, and visits to petrochemical companies. The input- and output-oriented multiplier models are used to assess overall and stage efficiencies. Using the efficiency values, the Malmquist productivity index is determined. The study examines unit productivity for the years 1395 to 1398, and the results indicate that most of the units experienced productivity growth during this period.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69623948","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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