University of HormozganInternational Journal of Industrial Engineering and Management Science2409-18719220220701A Comprehensive Framework of Information Technology Service Quality Assessment in a Manufacturing Company11019407610.22034/ijiems.2023.366110.1058ENAbbasSheikh AboumasoudiDepartment of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran0000-0003-3370-6555BehnamKhamoushpourDepartment of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, IranArashShahinDepartment of Management, University of Isfahan, Isfahan, IranShakibaKhademolqoraniDepartment of Industrial Engineering, Engineering faculty, Sheikh Bahaei University, Isfahan, IranJournal Article20221017With the advancement of technology, service quality has become strongly reliant on providing Information Technology (IT) services in all sections of an organization. Accordingly, a comprehensive framework is represented in this study to assess the quality of services supplied by the IT unit in a manufacturing company, which integrated the SERVQUAL model, the service quality gap, and IT service management metrics across the entire organization's supply chain. Regarding model reliability, a data-based decision model was designed in which big data analysis, including data mining and machine learning methods, was considered. Moreover, the essential analytical objectives for evaluating the IT unit, along with the data collection method and appropriate tools, were figured out. A steel production company was also used to express the efficiency and effectiveness of the proposed framework. The results determined SERVQUAL dimensions of reliability, responsiveness to tangible factors, sympathy, guarantee and the functional dimensions of problem-solving time, response time, and agreed service level are the most important, respectively.https://www.ijiems.com/article_194076_1c6979879704cb3d6432211655a73daf.pdfUniversity of HormozganInternational Journal of Industrial Engineering and Management Science2409-18719220220701Hybrid Truck-drone Delivery System with Pickup and Delivery Operations111919407710.22034/ijiems.2023.403462.1063ENRezaRashidIran university of science and technologyEbrahimTeimouryIran university of science and technologyJournal Article20230621In recent past years, drone delivery services gained tremendous attention from academia and logistic service providers, but it has some restrictions. For example, they have limited battery and payload capacities which reduce the efficiency of the delivery system. For that matter, coordination of ground vehicles and drones is proposed to take advantage of both trucks’ large capacity and the drone’s high speed, where the truck is used as a mobile depot and the drone is used to deliver parcels to customers. On the other hand, Due to the increase in e-commerce popularity, customers’ expectations for door-to-door services are increased. For this reason, we focused on the pickup and delivery problem in a truck and drone delivery system and proposed a mathematical model which aims to minimize the completion time. This work processes with a Branch-and-Bound and a heuristic Branch-and-Bound. To evaluate the performance of the proposed solution methods, numerous computational experiments are conducted, where the results show the efficiency of the proposed solution methods.https://www.ijiems.com/article_194077_58fa6aa009277908fad386b27a8af7ae.pdfUniversity of HormozganInternational Journal of Industrial Engineering and Management Science2409-18719220220701The Use of Simulated Annealing and Genetic Algorithm in Solving Resource Leveling Problem in Multi-project Mode202719407810.22034/ijiems.2023.367290.1059ENSeyed MahdiEbrahimiUniversity of Science and Arts of YazdMohammadKananizadehb PhD student of Industrial Engineering of Yazd University, Yazd, IranJournal Article20221025Having a functionally efficient plan with regards to Resource Leveling is among the significant determining factors when it comes to reducing the costs of any project; especially, when multiple projects are carried out simultaneously, this notion proves to have even more importance. In the present article, after exploring the general concept and notion of Resource Leveling and Problem Modelling in a single project, the problem will be scrutinized in multi-project mode. To proceeding with doing so, a mathematical model is proposed whose objective is to minimize the changes in the levels of different resources which are used by all projects.<br />Given the fact that Resource Leveling Problem is an NP-hard problem and reaching the optimized solution is not generally possible, methods such as Genetic Algorithm and Simulated Annealing Algorithm are used by which to reach an approximate optimal result. Additionally, to elucidate the quality of the eventual answer which was achieved by the two aforementioned algorithms, a real-life example of resource planning in a software company has been used.https://www.ijiems.com/article_194078_981b26619eb5cc6f9ddec14ac6715c25.pdfUniversity of HormozganInternational Journal of Industrial Engineering and Management Science2409-18719220220701Complete and Incomplete Hierarchical Hub Center Network Problem with Single Assignment283819407910.22034/ijiems.2023.299142.1045ENMohammadDoostmohammadiICT Research InstituteJournal Article20210810In this paper we present the problem of designing a three level hub center network. In our network, the top level consists of a complete network where a direct link is between all central hubs. The second and third levels are consisted of star networks that connect the hubs to central hubs and the demand nodes to hubs and thus to central hubs, respectively. Also we are modeling this problem in incomplete network environment. In this case, the top level consists of an incomplete network where a direct link between all central hubs is not necessary and an incomplete network may lead to having lower transportation costs. We propose mixed integer programming model for these problems and conduct a computational study for these two developed models by using the CAB data.<br />Hubs are facilities that used to consolidate and disseminate flow and serve as points for switching, transshipment and sorting flows in many-to-many distribution systems. In practice, the use of hubs can result in lower network costs, but it can be shifting to determine where hubs should be located or how demands should be allocated to them.https://www.ijiems.com/article_194079_b7e12a1f5f95d231a1838c8cb9282714.pdfUniversity of HormozganInternational Journal of Industrial Engineering and Management Science2409-18719220220701Imagined Speech Classification Accuracy and the Signal Acquisition Procedure394419408010.22034/ijiems.2023.399363.1061ENGholam RezaMohammad KhaniElectrical & IT department, Iranian Research Organization for Science and Technology
(IROST), Tehran, IranMohammad RezaAsghari BejestaniElectrical & IT department, Iranian Research Organization for Science and Technology (IROST), Tehran, Iran0000-0001-5360-392XJournal Article20230529Imagined speech recognition is one of the most interesting approaches to BCI development. A lot of works have been done in this area. Many different experiments have been designed and hundreds of combinations of feature extraction methods and classifiers have been examined. Reported classification accuracies range from the chance level to more than 90%. Based on non-stationary nature of brain signals, we have introduced 3 classification modes according to time difference in inter and intra-class samples. The modes can explain the diversity of reported results and predict the range of expected classification accuracies from the brain signal accusation procedure. In this paper, a few samples are illustrated by inspecting results of some previous works. It has been shown that, in current state of art researches on imagined word classification, if signal accusation schema falls in the mixed time mode, the accuracy can reach to more than 90 percent's, but for more realistic short and long time modes, it's hard to attain good results.https://www.ijiems.com/article_194080_f318c00ccbb5fd55e0af316a8011b4c9.pdf