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Öğe A Comprehensive Evaluation Model for Sustainable Supply Chain Capabilities in the Energy Sector(MDPI, ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND, 2024) Safaei, Mehdi; Yahya, Khalid; Al Dawsari, SalehThis study introduces a comprehensive model to evaluate multiple capabilities within the sustainable supply chain evaluation framework. The primary aim is to determine the significance of various capabilities in the context of sustainable supply chains. The research involved a sample of sixteen companies operating in Iran’s energy sector. The findings indicate that the majority of these companies are at level two in terms of capability. Therefore, it is recommended that these companies employ this model to assess their capability levels and identify any existing gaps. Methodologically, a checklist tool was used to refine the criteria using the fuzzy Delphi method. Subsequently, an appropriate model was chosen and developed by reviewing existing evaluation models. The criteria were compared and finalized using the Analytic Hierarchy Process. Finally, the criteria were further refined and validated through a fuzzy expert system, incorporating Adaptive Neuro-Fuzzy Inference System and Fuzzy Inference System. The developed model was then simulated and validated using MATLAB Simulink software (R2017b).Öğe Crisis management and the impact of pandemics on religious tourism(Dublin Institute of Technology, 2020) Mosier, William; Elhadary, Tariq; Elhaty, Ismail A. M.; Safaei, MehdiThe spread of the novel coronavirus (COVID-19) has caused a worldwide shockwave of fear and much misinformation leaving chaos in its wake. Holy shrines and other religious sites have a special place in the hearts and minds of many people. For example, the mosques in Makkah and Medina, Saudi Arabia typically accommodate over one hundred thousand Muslims daily. Due to the spread of COVID-19, both mosques were forced to shut their doors to pilgrims for health and safety reasons. This situation has saddened millions of Muslims all over the globe. The same situation applies to Qom City in Iran, Bethlehem on the West Bank, and the Vatican City. Precautionary actions have caused religious shrines to remain closed until further notice. The methodology used in this study is descriptive and multi-disciplinary. In this paper, the issue of COVID-19 is addressed from the perspective of medical science, chemistry, management science, economics, and religious sociology. This paper sheds light on the history of the virus, its effect on the global economy and crisis-management measures involving sacred places. The paper investigates how faith can expedite the recovery strategies of religious tourism, and consequently the tourism sector will follow suit. The paper elaborates on the potential impact of the pandemic on the future of religious tourism and how the psychological impact of closing Holy Shrines to pilgrims can be a strong driving force for a speedy recovery once the pandemic trickles off. © International Journal of Religious Tourism and PilgrimageÖğe Environmental Impact Assessment for Spatial Data Analysis in Disaster Management Using Machine Learning Multi-Criteria Resources(Springer Nature, 2024) Ashifa, K.M.; Babu, Jobi; Safaei, Mehdi; Arumugam, ThangarajaMany nations have created their own frameworks for disaster risk management (DRM) in response to the rising frequency of catastrophes that cause significant losses. Finding shelter is one of the most pressing demands of anyone impacted by a disaster. While the abundance of catastrophe data is already assisting in the saving of lives, it is necessary to quickly combine a broad variety of data in order to detect building damages, determine the need for shelter, and choose the best locations to set up emergency shelters or settlements. This research suggests a machine learning (ML) approach that seeks to fuse as well as quickly evaluate multimodal data in order to fill this gap and advance complete evaluations. This study suggests a unique approach to managing environmental disasters that is based on the analysis of geographical data using a machine learning model. Here, the input is a geospatial picture of a region that frequently experiences disasters, which is then smoothed and noise-removed. Then, a fuzzy clustering–based deep spatial reinforcement model (FCDSR) was used to choose the characteristics of the processed data. Multimodal Dirichlet allocation–based LSTM (long short-term memory) logistic correspondence algorithm (MDALLCA) was used to extract the chosen features. For various catastrophe datasets, experimental analysis is done in terms of prediction accuracy, precision, F-measure, and ROC. Our findings indicate possible locations with a high density of impacted people as well as infrastructure damage during the course of the crisis. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.Öğe Investigating the structure of strategies in developed countries to expand entrepreneurship and technology a case study: “US singularity university”(Institute of Advanced Scientific Research, Inc., 2020) Safaei, MehdiEntrepreneurship is the main foundation for the success and development of the university in all fields, because in the present century the pace of economic growth is based on innovation. Therefore, the support structures needed to grow those who transform the idea into a product must be provided. And, in fact, entrepreneurship is the link between knowledge and science, industry and market. To this end, empowering university students through promoting the knowledge, skills and entrepreneurial attitudes of all university graduates has been one of the main goals of developing countries. The increasing trend of university output, meeting all the needs of ordinary society, and the fluctuation of foreign exchange earnings in developing countries, necessitates the attention of wealthy and technophile universities. It is necessary to examine the structure of the strategies of the leading countries in the development of entrepreneurship and technology. This study examines the structure of one of the successful entrepreneurial universities with the new educational system and explores the strategies used in it. Finally, the feasibility of implementing such organizations in Iran (as one of the developing countries) has been examined with respect to the existing infrastructure. © 2020, Institute of Advanced Scientific Research, Inc.. All rights reserved.Öğe A Mathematical Model for Integrated Green Healthcare Supply Network Design(Igi Global, 2021) Nasrollahi, Meisam; Safaei, Mehdi; Mahmoodi, NooshinThis research presents a novel integrated mathematical programming model for green healthcare supply network design. A multi-graph integrated supply network was designed to meet real-world situations. Minimizing total cost and minimizing delivery time are considered as the objective functions. Since the considered problem is np-hard and the presented mathematical model is very complex and highly constrained, an innovative non-dominated ranked genetic algorithm (NRGA) called M-NRGA is developed to solve the real word problems. Three different selection procedures were implemented to improve the quality and diversity of solutions in the Pareto-front resulted from M-NRGA. Several numerical examples and a case study are solved to validate the model and performance evaluation of the solution algorithm. Four different performance metrics are implemented for performance evaluation of the solution algorithm. The quality of resulted solutions, the diversity of the solutions in the Pareto front are calculated for evaluation. The results are compared with two other meta-heuristic algorithms.Öğe A multi-objective model to allocate multiple facilities at proposed locations in the multi-floor organisation, using an improved genetic algorithm. Case study: Isfahan Governorate(Inderscience Publishers, 2021) Safaei, Mehdi; Nasrollahi, MeisamThe impressive role in the proper design of facility layout on productivity cannot be simply overlooked. So far, many models of the genetic algorithm have been introduced to solve such problems. The common approach of all these methods is to eliminate unacceptable answers. But given that unacceptable responses also have positive characteristics that can have a positive effect on next-generation fitness, this positive character can be exploited. In the multi-objective and multi-scale model presented, graded punishment is intended for such solutions, but will benefit from their positive features. Finally, the effectiveness of this method was evaluated by studying a case study. The results confirm the model's ability to improve the existing conditions. The main application of this model, in multi-layered organizations, is the allocation of several facilities to one location, depending on its capacity. It is also used to design workshop facility layouts. Copyright © 2021 Inderscience Enterprises Ltd.Öğe Neuromarketing approach: An overview and future research directions(Little Lion Scientific, 2020) Alsharif, Ahmed H.; Salleh, Nor Zafir Md; Baharun, Rohaizat B.I.N.; Safaei, MehdiNeuromarketing is the embryonic field of marketing science. Despite being controversial, it remains the most promising field to study genuine consumers' responses in front of the marketing stimuli such as sound, brand and so forth. Therefore, neuromarketing aims to study the relevant part in the human termed as 'brain' which is swayed by marketing stimuli. Undoubtedly, the researchers and academia can record and measured the brain activity through using the state-of-the-art neuroimaging techniques such as functional magnetic resonance imaging (fMRI), the electroencephalography (EEG), and other neuromarketing methods. Therefore, the academia and industry are relied on neuromarketing due to the widely acknowledged fact that the majority of our emotions and thinking takes place beyond the level of our awareness, thereby, the consumer purchase decisions are made in the subconscious mind which impact on their daily deliberations. This study reviews and discusses the most important techniques of neuromarketing (e.g., fMRI and EEG) to understand the consumer's brain responses. The findings of this study refer to that neuromarketing is pregnant with valuable information toward consumer decision-making. © 2005 - ongoing JATIT & LLSÖğe Optimizing Multi-Channel Green Supply Chain Dynamics with Renewable Energy Integration and Emissions Reduction(MDPI, ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND, 2024) Safaei, Mehdi; Al Dawsari, Saleh; Yahya, KhalidIn response to the global imperative of mitigating greenhouse gas emissions (GHGs) and the shifting landscape of business models toward multi-channel structures, this study delves into the intricacies of a green supply chain. Operating through both online and traditional channels with uncertain demands, the producer’s distribution strategy prompts an exploration of supply chain dynamics. Utilizing an integer programming model, this study calculates optimal prices, optimizes total profit, and minimizes transportation costs to curtail carbon dioxide emissions, depending on the transportation mode. Additionally, this study incorporates renewable energy sources into the production and transportation processes to further minimize carbon dioxide emissions. The integration of renewable energy not only supports environmental goals, but also contributes to the overall profitability of the supply chain by reducing energy costs. Employing a theoretical technique for linearization, the model, resolved through the Jimenez and TH methods, demonstrates efficacy in reconciling economic and environmental goals. The Jimenez method enables the transformation of fuzzy parameters into deterministic equivalents, allowing for a more reliable optimization during uncertainty, while the TH method provides an interactive fuzzy multi-objective approach, aligning the model’s dual objectives for both economic and environmental goals. Notably, when transportation costs to both markets are equal, the model prioritizes devices with a lower environmental impact, showcasing adaptability. Furthermore, the proposed solution empowers decision makers to influence pricing and enhance the entire supply chain’s profitability. In conclusion, this research offers nuanced insights, strategically aligning economic viability with environmental sustainability in the discourse on green supply chains.Öğe An overview on game theory and its application(IOP Publishing Ltd, 2020) Norozpour, Sajedeh; Safaei, MehdiThis research paper looks into Game Theory while immensely addressing the historical background of this theory. The document also gives an overview and definition of relevant terminologies related to this theory like a game, Nash equilibrium, and dominance which form the basis of the theory concept. It also focuses on mixed strategies, extensive games with both perfect and imperfect information, auction bidding, and their relevant practical application of the concept as applied in the field of economics. © 2020 IOP Conference Series: Materials Science and Engineering.Öğe Sustainable Survival Pyramid Model to Balance Four Factors of Cost, Quality, Risk and Time Limitation in Project Management under Uncertainty(UNIV PUNJAB, INST GEOL, QUID-E-AZAM CAMPUS, PO BOX NO 54590, LAHORE 00000, PAKISTAN, 2020) Safaei, MehdiThe final agreement on the timing of project completion is one of the obvious problems between project managers and their clients. There have been numerous reports of customers requesting shorter completion times than previously announced. This request will affect the three project factors of overall cost, final quality of the project, and risk of implementation. This paper proposes a multipurpose cumulative complex linear programming to minimize "project overhead," "increase projects total risk" and "increase overall project quality" due to “time constraints." In other words, the proposed study is fully implemented among the four goals mentioned to shorten the project duration. Computational experiments have also been used to evaluate the performance of the proposed model. The main objective of this paper is to optimize the integration of the four factors of the survival pyramid (time, cost, quality, and risk) in industrial projects simultaneously under uncertainty. An innovative solution approach based on the multi-objective genetic algorithm (NSGA-II) is presented. This model is then used to solve a problem in another study and its results, strengths, and weaknesses compared to the previous model are evaluated. The results show the performance of the proposed model in all four factors is better than the previous models.
