https://bgsiran.ir/journal/ojs-3.1.1-4/index.php/IJSASE/issue/feed International journal of sustainable applied science and engineering 2024-08-28T21:19:56+0330 Reza Lotfi reza.lotfi.ieng@gmail.com Open Journal Systems <p>International journal of sustainable applied science and engineering (IJSASE)</p> https://bgsiran.ir/journal/ojs-3.1.1-4/index.php/IJSASE/article/view/103 Feasibility Study for Construction Projects in Uncertainty Environment with Optimization Approach 2024-06-05T09:48:07+0330 Ali Bagheri Khoulenjani Abagherikhoulenjani@horizon.csueastbay.edu Mohammadamin Talebi m_talebi99@civileng.iust.ac.ir Elham Karim Zadeh karimzadehelham53@gmail.com <p>Construction projects are inherently complex and susceptible to various uncertainties throughout their lifecycle. These uncertainties can significantly impact project feasibility, leading to cost overruns, schedule delays, and reduced profitability. This paper explores the application of optimization approaches to enhance feasibility studies for construction projects in an uncertainty environment. We review existing literature on feasibility studies, uncertainty management, and optimization techniques in construction. The methodology proposes a framework for integrating uncertainty analysis and optimization into feasibility studies. A numerical example demonstrates the efficacy of the proposed framework by optimizing project schedules and resource allocation under different uncertainty scenarios. The results highlight the potential of optimization approaches to improve decision-making in feasibility studies, leading to more robust and reliable project assessments.</p> 2024-06-05T09:48:07+0330 ##submission.copyrightStatement## https://bgsiran.ir/journal/ojs-3.1.1-4/index.php/IJSASE/article/view/111 Comparing Performance of Insurance Companies Using Artificial Intelligence through Multi-Criteria Decision-Making Methods 2024-07-28T19:15:09+0330 Neda Mohammad Pour Khabbazi neda.pourkhabazi@gmail.com Hanieyeh Taghizadeh Fashkache Hanieyeh1372@yahoo.com <p>The insurance industry is characterized by intense competition and evolving customer expectations. Traditional performance metrics often fall short in capturing the complexities of the industry. This research aims to leverage artificial intelligence (AI) and multi-criteria decision making (MCDM) to evaluate the performance of insurance companies comprehensively. By integrating financial, operational, and customer-centric data, we develop an AI-driven framework to extract relevant features and construct a decision matrix. Subsequently, MCDM techniques are employed to rank insurance companies based on multiple criteria. The findings contribute to a deeper understanding of insurance company performance and provide valuable insights for strategic decision-making.</p> 2024-07-28T19:15:08+0330 ##submission.copyrightStatement## https://bgsiran.ir/journal/ojs-3.1.1-4/index.php/IJSASE/article/view/112 CHARISMA Coaching Model Framework 2024-07-30T14:36:28+0330 Saeid Rahimi Pamchalfi@gmail.com <p>Coaching is the art of facilitating the process of learning, developing and improving one's performance. Coaching can be considered a journey in which a coach helps another person to travel from where they are now to where they want to be in the future. Currently, coaching is recognized as a very effective way to help people to progress and succeed in business and life. Coaching is a dialogue-oriented relationship between two people of equal standing. A process that seeks to discover and create awareness in references through questioning. Adhering to ethical and professional principles, this service creates a safe environment to go deeper into feelings, thoughts and beliefs, so that what hinders personal or professional development is known, and by actualizing abilities, we can move forward towards the realization of goals.</p> 2024-07-30T14:36:28+0330 ##submission.copyrightStatement## https://bgsiran.ir/journal/ojs-3.1.1-4/index.php/IJSASE/article/view/114 Application of Large Language Models in the Industry 2024-08-11T10:32:17+0330 Fariba Sahebi Sahebi.kh@gmail.com <p>Large Language Models (LLMs) have emerged as transformative tools in various industrial applications. This paper examines the deployment of LLMs across different sectors, highlighting their capabilities in enhancing productivity, streamlining processes, and generating insights from vast amounts of unstructured data. Through a comprehensive literature review and a detailed exploration of methodologies employed in LLM applications, we delve into numerical results showcasing their effectiveness. The findings suggest that LLMs not only improve efficiency but also foster innovation and creativity within organizations. The conclusion emphasizes the potential future directions of LLMs in the industry, indicating a path toward further integration and advancements.</p> 2024-08-11T10:32:17+0330 ##submission.copyrightStatement## https://bgsiran.ir/journal/ojs-3.1.1-4/index.php/IJSASE/article/view/115 Designing a Fuzzy Inference System for Evaluating Job Satisfaction Using TOPSIS And Fuzzy ANP Techniques 2024-08-28T21:19:56+0330 Morteza Mohammadi Seif morteza.seif@gmail.com Hamed Kazemipoor h.kazemipoor@piau.ac.ir Mohsen Amra re.mohsenamra@gmail.com <p>Human resources (HR) are crucial production resources, encompassing all organisational staff members. Occupational issues have always been a priority for nations, intertwined with personal, social, and cultural aspects. This study develops an expert system to assess employee job satisfaction using the Minnesota Questionnaire, TOPSIS, and fuzzy ANP techniques. The survey is completed by client-facing employees from different sectors. ANP and FNAP techniques are discussed, followed by an investigation of TOPSIS and Fuzzy TOPSIS decision-making methods. MATLAB software is used to design the expert system. Results show that implementing satisfaction programs and addressing organisational issues are vital for employee job satisfaction. Meeting employees' needs increases satisfaction while neglecting them causes dissatisfaction. Organisations must prioritise preserving job satisfaction by addressing employee needs.</p> 2024-08-28T21:19:56+0330 ##submission.copyrightStatement##