Sharif University of TechnologyScientia Iranica1026-309832820250301Inventory control and price discount policies for perishable products with age and price-dependent demand2264010.24200/sci.2022.57315.5174ENFarzinBazrafshanDepartment of Industrial Engineering, Babol Noshiravani University of Technology, P.O. Box:47148-71167, Babol, Iran.SaeedEmamiDepartment of Industrial Engineering, Babol Noshiravani University of Technology, P.O. Box:47148-71167, Babol, Iran.HamidMashreghiDepartment of Industrial Engineering, Babol Noshiravani University of Technology, P.O. Box:47148-71167, Babol, Iran.Journal Article20201211In this paper, the inventory control and price discount problem for perishable products with price and age-dependent demand is investigated. The seller adjusts prices to influence demand and optimize profits through determining discount points, especially discount start time. A nonlinear mathematical model is proposed to find optimal order quantity, discount points, and prices before the product's expiration date to maximize profit. The developed model provides the number of discounts such that the shortage will not be allowed before the expiration date. It is observed that determining a proper discount start time provides an optimized sales plan with higher profit. Moreover, the Particle Swarm Optimization (PSO) and the Genetic Algorithm (GA) are applied to solve the problem. The Taguchi approach is used to find optimum control parameters of PSO and GA. To guarantee the validity of PSO and GA, the nonlinear model is solved by the Branch-And-Reduce Optimization Navigator (BARON) solver in General Algebraic Modeling System (GAMS) software. The performance of the algorithms is evaluated based on the real values of parameters for two perishable products (i.e., Cheese and Mayonnaise Sauce) and some random test problems. The computational results demonstrate that the proposed GA outperforms the PSO algorithm.https://scientiairanica.sharif.edu/article_22640_3ceae701da0625e3ba4f8750618e1ba0.pdfSharif University of TechnologyScientia Iranica1026-309832820250301Unit Nadarajah and Haghighi distribution: Properties and applications in quality control2402910.24200/sci.2021.57302.5167ENIsmailShahDepartment of Statistics, Quaid-i-Azam University, Islamabad 45320, Pakistan.BrikhnaIqbalDepartment of Statistics, Quaid-i-Azam University, Islamabad 45320, Pakistan.Muhammad FarhanAkramDepartment of Statistics, Quaid-i-Azam University, Islamabad 45320, Pakistan.SajidAliDepartment of Statistics, Quaid-i-Azam University, Islamabad 45320, Pakistan.SankuDeyDepartment of Statistics, St. Anthony's College, Shillong, India.Journal Article20201208In practice, the data related to rates and proportion may have excess of ones wherein the beta distribution does not fit well. To deal with the inflation of ones, this article introduces unit Nadarajah and Haghighi distribution. Besides deriving statistical properties of the proposed distribution, several estimation methods are discussed. In particular, maximum likelihood estimation, least squares estimation, weighted least squares estimation, maximum product of spacing, minimum spacing absolute distance estimation, minimum spacing absolute log-distance estimation, Cramer-Von-Mises, Anderson-Darling method and right-tail Anderson-Darling method are considered. Using real data sets, it is shown that the new distribution outperforms some well-known existing distributions. Furthermore, the application of the proposed distribution in quality control is also discussed. A control chart using unit Nadarajah and Haghighi distribution is constructed and its performance is evaluated using the average run length.https://scientiairanica.sharif.edu/article_24029_f9fc29138b61b3113be946d545d88b08.pdfSharif University of TechnologyScientia Iranica1026-309832820250301Reducing noise pollution by flexible job-shop scheduling with worker flexibility: Multi-subpopulation evolutionary algorithm2403010.24200/sci.2022.57813.5431ENMaryamHajibabaeiDepartment of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran.JavadBehnamianDepartment of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran.Journal Article20210226Flexible job-shop scheduling is one of the most critical production management topics. In this paper, it is also assumed job interruption due to the machine breakdown is allowed, and the processing time depends on the speed of the machines and requires both human and machine resources to process the jobs. Although, as the speed of the machine increases, the time of job’ completion reduces, an increase in speed results in an increase in noise pollution in the production environment, and with the aim of applying a cleaner production that is a preventative approach, it has been tried to reduce noise pollution by minimizing the increase in speed. After modeling the problem using the mixed -integer programming and solving it using the ε-constraint method, since the problem is NP-hard, a multi-subpopulation evolutionary algorithm is proposed to solve it. The results showed that considering the Mean Ideal Distance (MID) criterion, the ε-constraint method has a better performance than the proposed algorithm but considering other criteria the proposed algorithm has is better. Also, the proposed algorithm was compared with the NSGA-II in large-size instances and the computational results showed that the proposed algorithm performs better than the NSGA-II in most cases.https://scientiairanica.sharif.edu/article_24030_d99ea4a17470a486163a0351a7d12183.pdfSharif University of TechnologyScientia Iranica1026-309832820250301Group multiple attribute decision making using a modified TOPSIS method in the presence of interval data2403110.24200/sci.2022.56712.4869ENSamiraAbootalebiDepartment of Mathematics, Mobarakeh Branch, Islamic Azad University, Isfahan, Iran.AbdollahHadi-VenchehDepartment of Mathematics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran.AliJamshidiDepartment of Mathematics, Mobarakeh Branch, Islamic Azad University, Isfahan, Iran.Journal Article20200901Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is a well-known technique in multiple criteria decision making and has found several applications in recent years. However, as mentioned in literature TOPSIS has several shortcomings. In this paper, we present an extension of TOPSIS method to determine the weight of Decision Makers (DMs) in Group Multiple Attribute Decision Making (GMADM) problems with interval information. Our method is based on the concept that the best alternative is closer to the Positive Ideal Solution (PIS) and far away from the<br />Negative Ideal Solution (NIS), simultaneously. The contribution of the proposed method is that while it overcomes the shortcomings of the TOPSIS method it can be used to weight the decision making team and ranking the alternatives, as well. The method is illustrated through three examples.https://scientiairanica.sharif.edu/article_24031_ec5cabc15b178cda38e9b2eb32952bf1.pdfSharif University of TechnologyScientia Iranica1026-309832820250301A variable sampling interval multivariate exponentially weighted moving average control chart for monitoring the gumbel's bivariate exponential data2403210.24200/sci.2022.56544.4780ENFuPengXieSchool of Automation, Nanjing University of Science and Technology, Nanjing, China.XueLongHuSchool of Management and Institute of High-Quality Development Evaluation, Nanjing University of Posts and
Telecommunications, Nanjing, China.YuLongQiaoSchool of Automation, Nanjing University of Science and Technology, Nanjing, China.JinShengSunSchool of Automation, Nanjing University of Science and Technology, Nanjing, China.Journal Article20200804The general assumption in designing a multivariate control chart is that the multiple variables are independent and normally distributed. This assumption may not be tenable in many practical situations, because multiple variables with dependency often need to be monitored simultaneously to ensure the process is in control. The Gumbel's Bivariate<br />Exponential (GBE) distribution is considered to be a better model for skewed data with dependency in reliability analysis. In this paper, a Multivariate Exponentially Weighted Moving Average (MEWMA) scheme with Variable Sampling Interval (VSI) feature is developed to monitor the mean vector of GBE model. The Monte Carlo simulation is used to evaluate the Average Time to Signal (ATS) performance of the proposed VSI MEWMA GBE scheme for three di erent types of shifts. Some tables are presented to show the ATS performance of the proposed scheme with different designed parameters.<br />Additionally, both the zero-state and the steady-state ATS performance of the proposed scheme is compared with that of the conventional MEWMA chart with FSI (Fix Sampling Interval) feature. Comparative results show that the suggested scheme works better than its FSI counterpart in monitoring GBE data. Finally, a simulation example is provided to show that the VSI MEWMA GBE scheme performs well in monitoring GBE data.https://scientiairanica.sharif.edu/article_24032_931e8e7e0d4f4bcdc0f13f3bea663799.pdfSharif University of TechnologyScientia Iranica1026-309832820250301A new class of robust ratio estimators for finite population variance2403310.24200/sci.2022.57175.5100ENTolgaZamanDepartment of Mathematical Engineering, Faculty of Engineering and Natural Science, Gumushane University, Gumushane 29100, Turkey.HasanBulutDepartment of Statistics, Faculty of Science, Ondokuz Mayıs University, 55139 Samsun, Turkey.Journal Article20201115It is a general practice to use robust estimates to improve ratio estimators using functions of the parameters of an auxiliary variable. In this study, a new class of robust estimators based upon the Minimum Covariance Determinant (MCD) and the Minimum Volume Ellipsoid (MVE) robust covariance estimates have been suggested for estimating population variance in the presence of outlier values in the data set for the simple random sampling. The expression for the Mean Square Error (MSE) of the proposed class of estimators is derived from the first degree of approximation. The efficiency of the proposed class of robust estimators is compared with some competing estimators discussed in the literature, and found that proposed estimators are better than other mentioned estimators here. In addition, real data set and simulation studies are performed to present the efficiencies of the estimators. We demonstrate theoretically and numerically that the proposed class of estimators performs better than all other competitor estimators under all situations.https://scientiairanica.sharif.edu/article_24033_ebf1c7d3fd22600366c64fb77ee97a73.pdfSharif University of TechnologyScientia Iranica1026-309832820250301Coordination of a single-supplier multi-retailer supply chain via joint ordering policy considering incentives for retailers and utilizing economies of scale2405510.24200/sci.2022.57120.5072ENMehdiSeifbarghyDepartment of Industrial Engineering, Faculty of Engineering, Alzahra University, Tehran, Iran.MahnazShoeibDepartment of Industrial Engineering, Faculty of Engineering, Alzahra University, Tehran, Iran.DavarPishvaFaculty of Asia Pacific Studies, Ritsumeikan Asia Pacific University, Beppu, Japan.Journal Article20201118Lead-time fluctuations cause a low supply chain service level through increasing stock-outs. Lack of the supplier’s awareness of the retailers’ ordering policy is one of the main reasons for the lead-time fluctuations. In this paper, a two-echelon supply chain including single supplier, multiple retailers is studied under two scenarios of decentralized and centralized decision-making. In the first scenario, each retailer independently uses a continuous review inventory policy and the supplier does not know when each retailer will order. This policy prolongs order fulfillment by the supplier and increases order-processing costs. In the second scenario, retailers are encouraged to enter into a joint cooperation plan and change their ordering policy from independent continuous review policies to a joint periodic review policy. In this case, the supply chain can utilize the benefits of economies of scale via integrating and shipping several retailers’ orders. The study also determines range of the acceptable lead-time reduction by supplier and retailers for participating in the joint cooperation plan. The results show that joint cooperation plan creates more benefits for the supply chain in terms of cost and service level.https://scientiairanica.sharif.edu/article_24055_468bd4f0fd18cabe2082c995fcba6a95.pdfSharif University of TechnologyScientia Iranica1026-309832820250301Coordination in the supply chain considering total lead times and delivery times2405610.24200/sci.2022.57898.5464ENSeyed MohammadMirnourollahiSchool of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran.MasoudRabbaniSchool of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran.Journal Article20210312This study considers a two-echelon Supply Chain (SC) consisting of a single vendor and a single buyer by reducing delivery time. This paper examines delivery time optimization as an essential component of lead times. The length of delivery time and production time are studied simultaneously. The delivery time as a decision variable is considered in the proposed model. Reducing delivery time is considered a vital incentive factor in encouraging the buyer to participate in the coordinated model to guarantee profitability. A suggested mathematical model consisting of the profit functions of both participants (i.e., vendor and buyer) are investigated under two decision-making scenarios: the decentralized decision structure and coordinated decision structure. The analyses show that our proposed model ensures better performance for both participants and makes the whole process more profitable by an adequate sharing of risks between two participants. In other words, under the coordinated model, decreasing the delivery time and buyer's shortage costs and increasing the order quantity leads to an increase in the profit of the vendor and buyer.https://scientiairanica.sharif.edu/article_24056_a737f5162c1c3abfb9948bb7f8be0b3c.pdfSharif University of TechnologyScientia Iranica1026-309832820250301Risk assessment of medical devices used for COVID-19 patients based on a Markovian-based Weighted Failure and Mode Effects Analysis (WFMEA)2405710.24200/sci.2022.57493.5266ENMahdiehTavakoliSchool of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran.RezaMesbahiSchool of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran.SinaNayeriSchool of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran.FariborzJolaiSchool of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran.Journal Article20210108Medical devices are critical in the healthcare system and their failures can significantly impress the safety of patients, medical staff, and clinical engineers. With increasing COVID-19 pandemic in recent months, it is more necessary to assess the risks of the devices to avoid infection for patients, death, and severe hurts due to inactive and breakdown devices. The aim of this study is to assess medical device risks in general and pandemic situations with three main factors of the failure model analysis effect include occurrence, detection, and severity. Some sub-factors are defined and weighted using the fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) and fuzzy Best-Worst Method (BWM). Consequently, the Weighted Failure Mode and Effects Analysis (WFMEA) score of each failure is calculated as the Weighted Risk Priority Number (WRPN). Finally, steady-state probabilities of very low and low failures are calculated to consider the changes during the time. Results show that near half of the failures are scored in very low and low levels but in the long term, most of them transfer to medium level risk. It can be concluded that some preventive maintenance plans for these kinds of failures to avoid occurring the higher risk level for them in the future is necessary and the results can help medical device managers.https://scientiairanica.sharif.edu/article_24057_fcfb15373c9f64efdb9bee0e0a98c731.pdfSharif University of TechnologyScientia Iranica1026-309832820250301Pricing strategy for reproduction of worn-out ball and gate valves in oil and gas industry: Using game theory on four closed-loop supply chain scenarios2405810.24200/sci.2022.57124.5076ENMehdiSafariDepartment of Industrial Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran.MohammadFallahDepartment of Industrial Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran.HamedKazemipourDepartment of Industrial Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran.Journal Article20201122Collecting and remanufacturing worn-out products provide significant financial advantages. In this research, we examine how remanufacturing worn-out ball and gate valves, which are important pieces of equipment in the oil and gas industry, could improve the profitability of the closed-loop Supply Chain (SC). In this regard, four different scenarios for collecting and remanufacturing processes are considered: (1) The manufacturer collects the worn-out product from the consumers and remanufactures them; (2) The retailer collects the worn-out products and both manufacturer and retailer remanufacture them; (3) The third party collects the worn-out products and both manufacturer and third party remanufacture them, and (4) The manufacturer collects the worn-out products without remanufacturing them. To formulate the interactions of the Closed-Loop Supply Chain (CLSC) members under the four different scenarios, we use the Nash and Manufacturer-Stackelberg games. Accordingly, the optimal decision variables i.e., the acquisition price, wholesale price, and retail price are calculated under four scenarios. Then, the optimal solutions are compared in four scenarios. In addition, the optimal profit of the CLSC and members are obtained under the different scenarios. The results show that in the Nash game, Scenario 2 is the best scenario. However, in the Stackelberg game, Scenario 3 is the best scenario.https://scientiairanica.sharif.edu/article_24058_1c86c14337da15e38687fba9eab2e241.pdfSharif University of TechnologyScientia Iranica1026-309832820250301Multi support vector machine and image processing for diagnosis of coronary artery disease2406310.24200/sci.2022.57312.5173ENMohammad SadeghHasuni ShahrbabakDepartment of Industrial Engineering, Sharif University of Technology, Tehran, Iran.MajidKhedmatiDepartment of Industrial Engineering, Sharif University of Technology, Tehran, Iran.MahdiFathiDepartment of Information Technology and Decision Sciences, G. Brint Ryan College of Business, University of North Texas, Denton, Texas, USA.Journal Article20201211The optimal non-invasive test, Coronary Computed Tomography Angiography (CCTA), is to control Coronary Artery Disease (CAD). This paper proposes a developed algorithm called Multi Support Vector Machine (MSVM) applied in classification and diagnosing a common heart disease, CAD, utilizing the features extracted from the patients’ CCTA images through two image-processing-based approaches. These image-processing-based approaches including the quantification of cardiovascular vessels and the Auto Encoder (AE) network are utilized for the extraction of the features from the CCTA images. Then, a novel MSVM algorithm is developed for diagnosing heart diseases. A dataset from the Tehran Heart Center is utilized in addition to a collection of datasets from the literature to evaluate the performance of the proposed algorithms based on accuracy, precision, and recall performance measures. The proposed MSVM algorithm is compared with a number of existing methods in the literature where the results show that the proposed MSVM algorithm outperforms all the competing methods in terms of all the performance measures. In addition, it is concluded that the proposed MSVM algorithm performs much better than the classical Support Vector Machine (SVM) method under all the scenarios.https://scientiairanica.sharif.edu/article_24063_d7539337d1cf6e3dcc56592a82532d6c.pdfSharif University of TechnologyScientia Iranica1026-309832820250301Dynamic batch sentencing mechanisms for yield-based product acceptance determination with the simple linear profiles2409010.24200/sci.2022.57471.5263ENAtefeBanihashemiDepartment of Industrial Engineering, Yazd University, Yazd, Iran.Mohammad SaberFallah NezhadDepartment of Industrial Engineering, Yazd University, Yazd, Iran.AmirhosseinAmiriDepartment of Industrial Engineering, Shahed University, Tehran, Iran.Michael Boon ChongKhooSchool of Mathematical Sciences, Universiti Sains Malaysia, Penang, Malaysia.Journal Article20210107Acceptance sampling plan has been extensively used in batch sentencing to provide the manufacturer and the customer a general benchmark to meet their predetermined needs on the batch quality. This paper develops a flexible sampling procedure, based on the Spk index, for Simple Linear Profiles (SLP) by switching inspection rules. The plan parameters of the two suggested types of Quick Switching Sampling (QSS) systems, satisfying the desirable quality levels and constraining the manufacturers and the customer’s risks, are derived by solving an optimization model. The comparisons between the suggested systems and the existing sampling plans are discussed, in terms of the discriminatory power and the Average Sample Number (ASN) to show the better performance of the suggested systems. Finally, the suggested QSS systems are applied in the electronics industry.https://scientiairanica.sharif.edu/article_24090_8083a79c5dd6eae1b72514ff4df171c8.pdfSharif University of TechnologyScientia Iranica1026-309832820250301ICSI protocol advisor: A decision support system for infertility protocol suggestion2406110.24200/sci.2022.56987.5005ENZohrehTammimyDepartment of Information Technology, Faculty of Industrial Engineering, K.N. Toosi University of Technology, Tehran, Iran.SomayehAlizadehDepartment of Information Technology, Faculty of Industrial Engineering, K.N. Toosi University of Technology, Tehran, Iran.0000-0002-1947-7090Journal Article20201029Intra-Cytoplasmic Sperm Injection (ICSI) is one of the most common infertility treatments in which ovarian stimulation is carried out to extract the eggs from the ovaries. There are three, short, long, and pure treatment protocols of ovarian stimulation that vary by the type of medicine, the dosage of medicine, and the treatment term. Today, physicians choose an appropriate treatment protocol based on the patient's condition, such as age, and hormonal condition. This could be a relatively subjective and inaccurate method, particularly if the physician is not highly experienced. The present study investigates whether a decision support system can propose a more objective treatment protocol based on the patients’ data and data mining methods like logistic regression, decision tree, and Support Vector Machines (SVM). Such a system draws upon classification methods to propose proper treatment protocols for ICSI. Moreover, a separate module was developed to calculate the success rate of the proposed protocols. The system was tested with real data of treated patients at a Hospital in Tehran, Iran. The results showed the proposed system can predict the most proper treatment protocol with an accuracy of 81.90%. The proposed system can help inexperienced physicians to feel more confident about their advice.https://scientiairanica.sharif.edu/article_24061_167c8d70bd0989960474fa247c27e9d1.pdf