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495 results on '"Bozorgi-Amiri A"'

3. Improving Profitability of a Color Production Line by Breaking Down Bottlenecks: A Computer Simulation Approach

Author

Jamali, Amir, Ranjbar, Amirhossein, and Bozorgi-Amiri, Ali

Subjects
Mathematics - Optimization and Control
Abstract

Bottlenecks are one of the controversial issues in manufacturing companies. Managers and designers attempt to manage this trouble to improve efficiency in different ways. For example, expanding capacity is a prevalent solution to get rid of bottlenecks. In this paper, a color production line is chosen, which faces several challenges in its production line. This company attempts to distinguish and diminish the bottlenecks in the production line. The objective of this paper is to build a developed model of a production line to improve its profitability by breaking down its bottlenecks. Besides, the optimum number of operators with different utilizations is investigated in this paper. Furthermore, we considered the construction of new quality control in the station, which is the most time-wasting operation in the production line. The current study aims to apply computer simulation to examine the production line bottlenecks. In doing so, arena 14.00 software is used. Then the results are analyzed, and several managerial implications are presented., Comment: 10 pages

Published
2023

21. How metaheuristic algorithms can help in feature selection for Alzheimer’s diagnosis

Author

Farzaneh Salami, Ali Bozorgi-Amiri, and Reza Tavakkoli-Moghaddam

Subjects
metaheuristic algorithm, alzheimer’s disease, mri, machine learning, feature selection, data mining, Industrial engineering. Management engineering, T55.4-60.8
Abstract

Feature selection is the process of picking the most effective feature among a considerable number of features in the dataset. However, choosing the best subset that gives a higher performance in classification is challenging. This study constructed and validated multiple metaheuristic algorithms to optimize Machine Learning (ML) models in diagnosing Alzheimer’s. This study aims to classify Cognitively Normal (CN), Mild Cognitive Impairment (MCI), and Alzheimer’s by selecting the best features. The features include Freesurfer features extracted from Magnetic Resonance Imaging (MRI) images and clinical data. We have used well-known ML algorithms for classifying, and after that, we used multiple metaheuristic methods for feature selection and optimizing the objective function of the classification. We considered the objective function a macro-average F1 score because of the imbalanced data. Our procedure not only reduces the irreverent features but also increases the classification performance. Results showed that metaheuristic algorithms could improve the performance of ML methods in diagnosing Alzheimer’s by 20%. We found that classification performance can be significantly enhanced by using appropriate metaheuristic algorithms. Metaheuristic algorithms can help find the best features for medical classification problems, especially Alzheimer’s.

Published
2023
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42. Resilient banking: model-based assessment of business continuity policies on commercial banks.

Author

Bastan, Mahdi, Tavakkoli-Moghaddam, Reza, and Bozorgi-Amiri, Ali

Subjects
COVID-19 pandemic, ORGANIZATIONAL resilience, BANK management, STOCKHOLDER wealth, BANKING policy
Abstract

Purpose: Commercial banks face several risks, including credit, liquidity, operational and disruptive risks. In addition to these risks that are challenging for banks to control and manage, crises and disasters can exert substantially more destructive shocks. These shocks can exacerbate internal risks and cause severe damage to the bank's performance, leading banks to bankruptcy and closure. This study aims to facilitate achieving resilient banking policies through a model-based assessment of business continuity management (BCM) policies. Design/methodology/approach: By applying a system dynamics (SD) methodology, a systemic model that includes a causal structure of the banking business is presented. To build a simulation model, data are collected from a commercial bank in Iran. By presenting the simulation model of the bank's business, the consequences of some given crises on the bank's performance are tested, and the effectiveness of risk and crisis management policies is evaluated. Vensim Personal Learning Edition (PLE) software is used to construct the simulation model. Findings: Results indicate that the current BCM policies do not show appropriate resilience in the face of various crises. Commercial banks cannot create sustainable value for the banks' shareholders despite the possibility of profitability, as the shareholders lack adequate resilience and soundness. These commercial banks do not have the appropriate resilience for the next pandemic after coronavirus disease 2019 (COVID-19). Moreover, the robustness of the current banking business model is very fragile for the banking run crisis. Practical implications: A forward-looking view of resilient banking can be obtained by combining liquidity coverage, stable funding, capital adequacy and insights from stress tests. Resilient banking requires a balanced combination of robustness, soundness and profitability. Originality/value: The present study is a combination of bank business management, risk and resilience management and SD simulation. This approach can analyze and simulate the dynamics of bank resilience. Additionally, present of a decision support system (DSS) to analyze and simulate the outcomes of different crisis management policies and solutions is an innovative approach to developing effective and resilient banking policies. [ABSTRACT FROM AUTHOR]

Published
2024
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