Monireh Hosseini; Mahjoob Sadat Navabi
Articles in Press, Accepted Manuscript, Available Online from 06 February 2023
Abstract
With the development and widespread use of social networks among people, high-volume data is produced and the analysis of this data can be useful in many areas, including people's daily lives. Classification of this volume of data using traditional methods is a very difficult, time-consuming, and low-accuracy ...
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With the development and widespread use of social networks among people, high-volume data is produced and the analysis of this data can be useful in many areas, including people's daily lives. Classification of this volume of data using traditional methods is a very difficult, time-consuming, and low-accuracy task, therefore, using sentiment analysis techniques, people's opinions can be effectively summarized and categorized. To this end, we propose an algorithm that combines Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA). The reason for combining the two algorithms is that the GSA has a good ability to search overall, but in the last iterations, it has a low speed in exploiting the search space. Since the PSO algorithm has a special ability to exploit the search space, this algorithm is used in the exploitation phase to solve the problem. The accuracy obtained from our proposed algorithm (PSO-GSA) shows an improvement in the accuracy of the GSA algorithm.
Alireza Aliahmadi; Javid Gharemani-Nahr; Hamed Nozari
Articles in Press, Accepted Manuscript, Available Online from 07 February 2023
Abstract
This paper discusses the modeling and solution of a flexible flow shop scheduling problem with forward and reverse flow (FFSP-FR). The purpose of presenting this mathematical model is to achieve a suitable solution to reduce the completion time (Cmax) in forward flow (such as assembling parts to deliver ...
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This paper discusses the modeling and solution of a flexible flow shop scheduling problem with forward and reverse flow (FFSP-FR). The purpose of presenting this mathematical model is to achieve a suitable solution to reduce the completion time (Cmax) in forward flow (such as assembling parts to deliver jobs to the customer) and reverse flow (such as disassembling parts to reproduce parts). Other important decisions taken in this model are the optimal assignment of jobs to each machine in the forward and reverse flow and the sequence of processing jobs by each machine. Due to the uncertainty of the important parameters of the problem, the Fuzzy Jiménez method has been used. The results of the analysis with CPLEX solver show that with the increase in the uncertainty rate, due to the increase in the processing time, the Cmax in the forward and reverse flow has increased. GA, ICA and RDA algorithms have been used in the analysis of numerical examples with a larger size due to the inability of the CPLEX solver. These algorithms are highly efficient in achieving near-optimal solutions in a shorter time. Therefore, a suitable initial solution has been designed to solve the problem and the findings show that the ICA with an average of 273.37 has the best performance in achieving the near-optimal solution and the RDA with an average of 31.098 has performed the best in solving the problem. Also, the results of the T-Test statistical test with a confidence level of 95% show that there is no significant difference between the averages of the objective function index and the calculation time. As a result, the algorithms were prioritized using the TOPSIS method and the results showed that the RDA is the most efficient solution algorithm with a utility weight of 0.9959, and the GA and ICA are in the next ranks. Based on the findings, it can be said that industrial managers who have assembly and disassembly departments at the same time in their units can use the results of this research to minimize the maximum delivery time due to the reduction of costs and energy consumption, even though there are conditions of uncertainty
Hamid Reza Aghamiri; Esmaeil Mehdizadeh; Habib Reza Gholami
Articles in Press, Accepted Manuscript, Available Online from 07 February 2023
Abstract
Today, the proper and effective performance of employees is one of the keys to the success of organizations. Good performance refers to high efficiency, quality, profitability, and customer orientation. One of the most important duties of human resource managers is to design and establish employee performance ...
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Today, the proper and effective performance of employees is one of the keys to the success of organizations. Good performance refers to high efficiency, quality, profitability, and customer orientation. One of the most important duties of human resource managers is to design and establish employee performance evaluation systems. Since qualitative indices have a major share of these indices, judgmental methods are generally used for ranking them. Decision makers assign weights to these indices based on their attitudes and rank the employees. Hence, these methods fail to fully explain the performance of organizations’ employees and are influenced by some degrees and levels of ambiguity. Fuzzy logic methods are highly useful for resolving the ambiguities in these alternatives. In this paper, we propose an employee performance evaluation method with a type-2 fuzzy ranking approach. In our proposed method, a job ID is designed based on optimal models while an employee ranking method is developed and explained using the trapezoidal interval type-2 fuzzy ranking model introduced by Chen et al. 2012. In the end, the proposed method is utilized for the performance evaluation of employees in a real company.
Ali Eslamibidkoli; Mohammad Reza Sadeghi Moghadam; Tahmurath Hasangholipour
Articles in Press, Accepted Manuscript, Available Online from 08 February 2023
Abstract
Emerging companies or start-ups are growing rapidly and their number is increasing every day so that the number of knowledge-based and start-up companies in Iran has increased from about 55 companies in 2013 to more than 5965 companies in 2021. The capital element is the main and most productive factor ...
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Emerging companies or start-ups are growing rapidly and their number is increasing every day so that the number of knowledge-based and start-up companies in Iran has increased from about 55 companies in 2013 to more than 5965 companies in 2021. The capital element is the main and most productive factor for the success of start-ups and choosing the right financing method to achieve success is inevitable. The start-up literature offers a number of ways to finance entrepreneurs that are often presented in other geographies (often in startups operating in the United States) and those models cannot be accepted as non-native. Developing a strategic local financing framework based on the tacit knowledge gained by emerging digital startups can address this issue. Based on this, the present study aims to fill the existing gaps by designing a strategic financing framework for digital start-ups based on local criteria in order to be effective in the success of digital start-ups. The statistical population of the quality sector includes entrepreneurs and digital business owners, 30 of whom were identified by snowball method and interviewed in a semi-authorized manner. The statistical population of the quantitative section includes 166 digital businesses operating in Tehran science and technology parks that have been selected using Cochran's formula in a simple random method. To collect data, the method of library review and interviews with experts and finally the distribution of questionnaires have been used. The analysis of the findings in the qualitative stage was performed with a thematic analysis approach and the results showed that 101 open codes were categorized in 17 sub-themes and 17 sub-themes were placed in 5 main themes. In the quantitative stage, confirmatory factor analysis and structural equation modeling with LISREL software were used. The results showed that five main factors including corporate factors, macro environmental factors, investment factors, business valuation factors and idea and product factors are effective in designing digital business financing strategy.
Shaaban ALI Hoseinpour; Behrouz Afshar Nadjafi; Seyed Taghi Akhavan Niaki
Articles in Press, Accepted Manuscript, Available Online from 19 April 2023
Abstract
The firefighter problem on a graph, depending on the environment, the graph can be continuous or discrete, which includes tree, cubic, regular and irregular graphs, etc., is described in such a way that by starting a fire from a series of vertices, the goal is to contain the fire with the maximum number ...
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The firefighter problem on a graph, depending on the environment, the graph can be continuous or discrete, which includes tree, cubic, regular and irregular graphs, etc., is described in such a way that by starting a fire from a series of vertices, the goal is to contain the fire with the maximum number of vertices saved. Our main innovation is to model the firefighter problem with on a bi- objective model, which simultaneously saves the maximum number of vertices with the minimum number of firefighters. The firefighter problem is a type of Np-hard problem, and because we defined the problem as a bi-objective problem and added three constraints to it, the problem became more difficult, and the weighted bi-objective model is also Np-hard. To solve the NP-hard problem, we used multi-objective optimization4 such as Goal Programming (GP), ε- Constraint, Global Criterion Approach, Weighting Sum Method methods. To prove the performance of our method, we used a randomly generated sample.
Ehsan Mardan; Rezvane Kashani; Reza Kamranrad
Articles in Press, Accepted Manuscript, Available Online from 19 April 2023
Abstract
Supply chains in the world are increasingly exposed to disruptions caused by disasters in every part of the world. The emergence of risk in today's business environment due to globalization, disruptions, poor infrastructure, forecast errors and various uncertainties affects every management decision. ...
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Supply chains in the world are increasingly exposed to disruptions caused by disasters in every part of the world. The emergence of risk in today's business environment due to globalization, disruptions, poor infrastructure, forecast errors and various uncertainties affects every management decision. The present study was an attempt to propose an emergency order and production planning for a multi-product multi-item problem where products are made up of several ingredients. A side from the main supplier, the backup supplier can be used to supply each component where orders must be delivered within a certain time interval (specified time window). In the present study attempts are made to use sourcing strategies to realize supply chain flexibility under disruptions. A scenario-based mathematical model encompassing different uncertainties such as those arising from disruption and operational risks is formulated. A case study analysis is carried out to appraise the output of risk attitudes adopted by different decision-makers (both risk-neutral and risk-averse). The present study presents strategies to create flexible supply bases that diminish the cost of the worst scenario in the face of supply chain risks. By increasing the number of primary and supporting suppliers, VAR and C-VR values will increase, so the management offer is that the number of suppliers should be kept constant within acceptable limits to prevent a sharp increase in the number of suppliers. Suppliers should release orders in time by establishing time windows and setting deadlines in order to receive orders. Also, this paper shows that the values of VAR and C-VR decrease with the increase of primary supply capacity, and with the increase of primary supply capacity, costs are reduced by about 99%, which reduces the effect of disruption on the capacity of primary suppliers.