@article { author = {Aria, S. Sina and Torabi, S. Ali and Nayeri, Sina}, title = {A Hybrid Fuzzy Decision-Making Approach to Select the Best online-taxis business}, journal = {Advances in Industrial Engineering}, volume = {54}, number = {2}, pages = {99-120}, year = {2020}, publisher = {University of Tehran}, issn = {2783-1744}, eissn = {2783-1744}, doi = {10.22059/jieng.2021.320051.1754}, abstract = {In the recent decade, significant growth of internet-based platforms and changes in people’s moving preferences has led to an increase in the electronic taxis businesses. Hence, investigating the factors affected by such businesses can help increase their profits and, at the same, time their customers’ satisfaction level. In this study, a hybrid fuzzy decision-making approach is proposed to examine the best online-taxis business selection problem. The proposed framework firstly determines the interrelationships between criteria and sub-criteria, by applying the Fuzzy Decision making trial and evaluation laboratory (FDEMATEL) method. Then, the weights of the criteria and sub-criteria are calculated using an integrated Fuzzy Best-Worst Method (FBWM) and the Fuzzy Analytic network process (FANP). In this regard, at first, the local weights of indicators are calculated using the FBWM regardless of interrelationships between them. Then, the final (i.e. global) weights of indicators, considering their interrelationships, are measured employing the FANP method. Afterwards, the feasible alternatives are prioritized by employing the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) method. For each step of the proposed framework, a questionnaire is designed and distributed between experts. The results show that the most important criteria and sub-criteria for passengers are cost and reasonable price, respectively. Finally, some managerial insights are provided.}, keywords = {Startup-Based Business,Online-taxis,Multiple-attribute decision-making,Hybrid methods}, url = {https://aie.ut.ac.ir/article_81727.html}, eprint = {https://aie.ut.ac.ir/article_81727_848c2a7f898d2cf3eac0d52b0c99441f.pdf} } @article { author = {Dehghan Dehnavi, Mohammad Ali and Bahrololoum, Mohammad Mahdi and Peymany Foroushany, Moslem and Raeiszadeh, Sayyed Ali}, title = {Portfolio Selection Optimization Problem Under Systemic Risks}, journal = {Advances in Industrial Engineering}, volume = {54}, number = {2}, pages = {121-140}, year = {2020}, publisher = {University of Tehran}, issn = {2783-1744}, eissn = {2783-1744}, doi = {10.22059/jieng.2021.321882.1759}, abstract = {Abstract: Portfolio selection is of great importance among financiers, who seek to invest in a financial market by selecting a portfolio to minimize the risk of investment and maximize their profit. Since there is a covariant among portfolios, there are situations in which all portfolios go high or down simultaneously, known as systemic risks. In this study, we proposed three improved meta-heuristic algorithms namely, genetic, dragonfly, and imperialist competitive algorithms to study the portfolio selection problem in the presence of systemic risks. Results reveal that our Imperialist Competitive Algorithm are superior to Genetic algorithm method. After that, we implement our method on the Iran Stock Exchange market and show that considering systemic risks leads to more robust portfolio selection. . Results reveal that our Imperialist Competitive Algorithm are superior to Genetic algorithm method. After that, we implement our method on the Iran Stock Exchange market and show that considering systemic risks leads to more robust portfolio selection.}, keywords = {Portfolio Selection,Systemic Risks,Genetic Algorithm,Imperialist competitive algorithm}, url = {https://aie.ut.ac.ir/article_81728.html}, eprint = {https://aie.ut.ac.ir/article_81728_cab0fdd2da76993b72c911d1aaaff114.pdf} } @article { author = {Motalebi, Maedeh and Nasiri, Mohammad Mahdi and Shakouri G., Hamed and Taghaddos, Hosein}, title = {A Simulation-Optimization Model for Solar PV Panel Selection Under Solar Irradiance and Load Uncertainty}, journal = {Advances in Industrial Engineering}, volume = {54}, number = {2}, pages = {141-164}, year = {2020}, publisher = {University of Tehran}, issn = {2783-1744}, eissn = {2783-1744}, doi = {10.22059/jieng.2021.323127.1760}, abstract = {In this reserach, a multi-objective model is presented considering simulated behavior of high-efficiency rooftop solar PV panels in factory, which are among the largest producers of green-house gases. The paper proposes a simulation-optimization approach is used to maximize the net present value (NPV) of economic benefits along with minimizing the payback period (PBP) of the investment, and maximizing solar energy consumption rate (SECR). In addition, the solar PV panels degradation and maintenance cost, as well as the uncertainty in solar irra-diance and demand load, are also considered. The study consists of two scenarios, in the first of which both electricity tariffs and feed-in-tariffs (FiT) are fixed by a long-term contract. The second scenario investigates the situation in which subsidies on electricity tariff are removed. The best type of panels are found in each scenario considering trade-off between objective functions. The preferred trade-off solution in the first scenario, with 2% increase in PBP, achieves more than 10% growth in NPV which is about $15000 in a year. In the second sce-nario, with only about 0.2% decrease in NPV and 3% increase in PBP, the preferred solution attains 9% increase in SECR.}, keywords = {simulation,Rooftop solar PV panels,Electricity tariffs policy,maintenance,Uncertainty}, url = {https://aie.ut.ac.ir/article_81729.html}, eprint = {https://aie.ut.ac.ir/article_81729_19c2e064e43d9c88b524f60e93974242.pdf} } @article { author = {Jolai, Fariborz and Hashemi, Parisa and Heydari, Jafar and Bakhshi, Alireza and Keramati, Abbas}, title = {Optimizing a Reverse Logistics System by Considering Quality of Returned Products}, journal = {Advances in Industrial Engineering}, volume = {54}, number = {2}, pages = {165-184}, year = {2020}, publisher = {University of Tehran}, issn = {2783-1744}, eissn = {2783-1744}, doi = {10.22059/jieng.2021.323213.1762}, abstract = {Coordination is one of the critical issues in remanufacturing systems that can persuade supply chain parties to make optimal centralized decisions leading to higher profits. Accordingly, this paper aims to examine a reverse logistics system, including one manufacturer along with a collector who collects used products based on the consumers' willingness to return such products. Consumers’ willingness is dependent on the take-back price, which is adjusted based on various quality levels affecting the processing cost of the collected items. This study developed mathematical models under both decentralized and centralized scenarios. Besides, to align the interests of both members and better profit-sharing, a cost-sharing contract is implemented. According to the results, in the coordination model, the take-back price of the high-quality level is increased compared to the decentralized model while the take-back price of the low-quality level is decreased. Hence, it suggests collecting and repairing higher-quality products to achieve higher profits for the whole system. Besides, the paper provides valuable suggestions for managers to resolve the conflicts of interest among participants of reverse logistics systems in an efficient manner.}, keywords = {Reverse logistics,Quality of Returned Product,coordination,Recycling Strategy,Cost-Sharing Contract}, url = {https://aie.ut.ac.ir/article_81730.html}, eprint = {https://aie.ut.ac.ir/article_81730_2b4b1a7b6af359bca23d77895b0acc2a.pdf} } @article { author = {Alimohammadi Ardekani, Majid and Kabiri Naeini, Mehdi}, title = {Designing a Multi-Level Blood Supply Chain Network with the Likelihood of Shortage and Perishability in the Inventory}, journal = {Advances in Industrial Engineering}, volume = {54}, number = {2}, pages = {185-204}, year = {2020}, publisher = {University of Tehran}, issn = {2783-1744}, eissn = {2783-1744}, doi = {10.22059/jieng.2021.323832.1764}, abstract = {Blood is a vital substance for human life. A blood unit goes through various stages from its donation by the donor until its reception by the person in need of blood. This process can be explored the context of supply chain management. For this purpose, a mathematical model is developed in this study to design a blood supply chain network. The noticeable feature of this network is the inclusion of the shortage and perishability of blood products as two important indicators. The mathematical model proposed in this regard has the two objective functions of minimizing the blood supply chain costs and, at the same time, maximizing the average amount of blood sent from blood centers to hospitals. The model examines the problem in the case of a single product. The modified weighted Chebyshev, the improved version of ε-constraint (AUGEMCON2), and unscaled goal programming are used to solve the mathematical model. Then, to evaluate and compare the proposed solution methods and select the best one, the statistical hypothesis test and the VIKOR technique are used respectively. The results show that the model proposed for the blood supply chain is efficient and acceptable; hence, it can be of benefit in different types of blood supply chains where the shortage and perishability of blood products are taken into account.}, keywords = {Blood supply chain management,Multi-objective decision-making,VIKOR Technique,Exact solution methods,Shortage and perishability of blood products}, url = {https://aie.ut.ac.ir/article_81731.html}, eprint = {https://aie.ut.ac.ir/article_81731_cc269f4b220dcaa9e96a7802b33660ec.pdf} } @article { author = {Shirani Bidabadi, Hossein and Shishebori, Davood and Ahmadi Yazdi, Ahmad}, title = {Multivariate Process Incapability Index Considering Measurement Error in Fuzzy Environment}, journal = {Advances in Industrial Engineering}, volume = {54}, number = {2}, pages = {205-220}, year = {2020}, publisher = {University of Tehran}, issn = {2783-1744}, eissn = {2783-1744}, doi = {10.22059/jieng.2021.323883.1765}, abstract = {Process Capability Indices (PCI) show that the process conforms to the specification limits; when the product quality depends on more than one characteristic, Multivariate Process Capability Indices (MCPI) are used. By modifying in the process capability indices, the process incapability indices are created; these indices then provide information about the accuracy and precision of the process separately. In the real world, in most cases, the parameters cannot be specified precisely; therefore, the use of fuzzy sets can solve this problem in statistical quality control. The purpose of this paper is to present, for the first time, a Multivariate Process Incapability Index by considering the measurement error in a fuzzy environment. The presented index is shown for practical examples solved by considering Triangular Fuzzy Numbers; then the capability of the model is compared to the time when fuzzy logic is not used. The obtained results emphasize that ignoring the measurement error also leads to the incorrect calculation of process capability, causing a lot of damage to manufacturing industries, especially high-tech ones.}, keywords = {Fuzzy multivariate process incapability Index,Fuzzy Mmeasurement Error,Multivariate normal distribution,Fuzzy logic}, url = {https://aie.ut.ac.ir/article_81732.html}, eprint = {https://aie.ut.ac.ir/article_81732_3b981eaa0a98608d3a938fea31a1eae3.pdf} }