Auflistung nach Autor:in "Yazdi, Amir Karbassi"

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A binary differential evolution algorithm for airline revenue management: a case study
(Springer, 2020) Yazdi, Amir Karbassi; Kaviani, Mohamed Amin; Hanne, Thomas; Ramos, Andres
01A - Beitrag in wissenschaftlicher Zeitschrift
A credit rating model in a fuzzy inference system environment
(MDPI, 2019) Yazdi, Amir Karbassi; Hanne, Thomas; Wang, Yong J.; Wee, Hui-Ming
One of the most important functions of an export credit agency (ECA) is to act as an intermediary between national governments and exporters. These organizations provide financing to reduce the political and commercial risks in international trade. The agents assess the buyers based on financial and non-financial indicators to determine whether it is advisable to grant them credit. Because many of these indicators are qualitative and inherently linguistically ambiguous, the agents must make decisions in uncertain environments. Therefore, to make the most accurate decision possible, they often utilize fuzzy inference systems. The purpose of this research was to design a credit rating model in an uncertain environment using the fuzzy inference system (FIS). In this research, we used suitable variables of agency ratings from previous studies and then screened them via the Delphi method. Finally, we created a credit rating model using these variables and FIS including related IF-THEN rules which can be applied in a practical setting.
01A - Beitrag in wissenschaftlicher Zeitschrift
A decision-support approach under uncertainty for evaluating reverse logistics capabilities of healthcare providers in Iran
(Emerald, 2020) Yazdi, Amir Karbassi; Fernandes Wanke, Peter; Hanne, Thomas; Bottani, Eleonora
Purpose – This paper aims to assess and prioritize manufacturing companies in the healthcare industry based on critical success factors (CSFs) of their reverse logistics (RL). The research involves seven medical device companies located in the Tehran Province, Iran. Design/methodology/approach – To identify and prioritize companies based on CSFs of RL, the study proposes a three-phase decision-making framework that integrates the Delphi method, the best-worst method (BWM) and the Additive Ratio Assessment (ARAS) method with Z-numbers. The weights required for this method are obtained by a variant of the BWM based on Z-numbers, denoted as Z-numbers Best-Worst Method, or ZBWM. Since decision-makers face an uncertain environment, Z-numbers, which are a kind of fuzzy numbers, are applied. Findings – First, after customizing CSFs by the Delphi method and obtaining 15 CSFs of RL, these are ranked by the hybrid BWM-ARAS method with Z-numbers. Results reveal which company appears to perform best with respect to their RL implementations. Based on this result, healthcare device companies should choose the highest priority company based on the selected RL CSFs and results from using the BWM-ARAS method with Z-numbers. Originality/value - The contribution of this paper is using a hybrid ARAS-BWM method based on Z-numbers. Each of these methods has some merits compared to other similar methods. The combination of these methods contributes a new approach for prioritizing companies based on RL CSFs with high accuracy and reliability.
01A - Beitrag in wissenschaftlicher Zeitschrift
A hybrid model for ranking critical successful factors of lean six sigma in the oil and gas industry
(Emerald, 2021) Yazdi, Amir Karbassi; Hanne, Thomas; Osorio Gómez, Juan Carlos
Purpose - The aim of this paper is to find and prioritise multiple critical success factors (CSFs) for the implementation of LSS in the oil and gas industry. Design/methodology/approach - Based on a preselected list of possible CFSs, experts are involved in screening them with the Delphi method. As a result, 22 customised CSFs are selected. To prioritise these CSFs, the step-wise weight assessment ratio analysis (SWARA) method is applied to find weights corresponding to the decision-making preferences. Since the regular permutation-based weight assessment can be classified as NP-hard, the problem is solved by a metaheuristic method. For this purpose, a genetic algorithm (GA) is used. Findings - The resulting prioritisation of CSFs helps companies find out which factors have a high priority in order to focus on them. The less important factors can be neglected and thus do not require limited resources. Research limitations/implications - Only a specific set of methods have been considered. Practical implications - The resulting prioritisation of CSFs helps companies find out which factors have a high priority in order to focus on them.Social implicationsThe methodology supports respective evaluations in general. Originality/value - The paper contributes to the very limited research on the implementation of LSS in the oil and gas industry, and, in addition, it suggests the usage of SWARA, a permutation method and a GA, which have not yet been researched, for the prioritisation of CSFs of LSS.
01A - Beitrag in wissenschaftlicher Zeitschrift
Analyzing the investment behavior in the Iranian stock exchange during the COVID-19 pandemic using hybrid DEA and data mining techniques
(Hindawi, 2022) Sarfaraz, Amir Homayoun; Yazdi, Amir Karbassi; Hanne, Thomas; Gizem, Özaydin; Khalili-Damghani, Kaveh; Husseinagha, Saiedeh Molla
The main purpose of this paper is to investigate the effects of COVID-19 regarding the efficiency of industries based on data in the Tehran stock market. A hybrid model of Data Envelopment Analysis (DEA) and data mining techniques is used to analyze the investment behavior in Tehran stock market. Particularly during the COVID-19 pandemic, many companies face financial crises. That is why companies with inferior performance must be benchmarked with efficient companies. First, the financial data of investments on selective companies are analyzed using data mining approaches to recognize the behavioral patterns of investors and securities. Second, customers are clustered into 3 selling and 4 buying groups using data mining techniques. Then, the efficiency of active companies in stock exchange is evaluated using input-oriented DEA. The results indicate that, among 23 industries listed on the stock market in Iran, solely nine were efficient in 2019. Moreover, in 2020, the number of efficient industries further decreased to six industries. Comparing the obtained results with those of another study which was conducted in 2018 by other researchers revealed that COVID-19 strongly affects the performance of an industry and some industries which were efficient in the past such as the bank industry became inefficient in the following year.
01A - Beitrag in wissenschaftlicher Zeitschrift
Evaluating the performance of Colombian banks by hybrid multicriteria decision making methods
(Vilnius Gediminas Technical University, 2020) Yazdi, Amir Karbassi; Hanne, Thomas; Osorio Gómez, Juan Carlos
The aim of the study in this paper is to show how the performance of banks can be evaluated by ranking them based on Balanced Scorecard (BSC) and Multicriteria Decision Making (MCDM) methods. Nowadays, assessing the performance of companies is a vital work for finding their weaknesses and strengths. The banking sector is an important area in the service sector. Many people want to know which bank performs best when entrusting their money to them. For assessing the performance of banks, BSC can be used. This method helps to translate strategic issues to meaningful insights for the respective financial institutions. After that, the banks will be ranked based on performance indicators by the Weighted Aggregated Sum Product Assessment (WASPAS) method. Because this method is based on a decision matrix, weights are required. To find such weights, the Step-wise Weight Assessment Ratio Analysis (SWARA) method is applied. The results show that the International Bank of Colombia has a much better performance than other Colombian banks. Besides, further insights regarding the evaluation process based on BSC, SWARA, and WASPAS are obtained.
01A - Beitrag in wissenschaftlicher Zeitschrift
Finding the best third-party logistics in the automobile industry
(Hindawi, 2018) Yazdi, Amir Karbassi; Hanne, Thomas; Osorio Gómez, Juan Carlos; García Alcaraz, Jorge Luis
Given the current economic climate, many companies are considering outsourcing some activities to reduce costs and to focus on their core competency; thus, by adopting a competency-focused approach they enhance their chances to survive in a growing and competitive market. Third-Party Logistics (3PL) is a system that facilitates logistic activities. First, however, the organizations need to assess which companies are suitable for outsourcing. The aim of this paper is to depict a structural system for 3PL selection and validate it in real-world automobile companies. We use the Delphi method to determine criteria for 3PL selection and apply Evaluation by an Area-based Method for Ranking (EAMR) to prioritize the candidate alternatives. This method is used in combination with a Shannon Entropy based approach for determining the required weights. Computational analysis shows which criteria and companies have high priority, and based on that candidate alternatives for outsourcing are evaluated. The results suggest how automobile companies select 3PL companies and allocate their work to them.
01A - Beitrag in wissenschaftlicher Zeitschrift
Supplier selection in the oil & gas industry: a comprehensive approach for multi-criteria decision analysis
(Elsevier, 2021) Yazdi, Amir Karbassi; Fernandes Wanke, Peter; Hanne, Thomas; Abdi, Farshid; Sarfaraz, Amir Homayount
01A - Beitrag in wissenschaftlicher Zeitschrift