Research Paper
Scheduling
Saeideh Naderi; Mohsen Vaez-Ghasemi; farzad movahedi sobhani
Abstract
The Resource-Constrained Project Scheduling Problem (RCPSP) is a general one in scheduling which possesses various applications in production, production scheduling, project managing and other criteria. This issue has been studied since 1960 and is very complicated. In this study, the common presuppositions ...
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The Resource-Constrained Project Scheduling Problem (RCPSP) is a general one in scheduling which possesses various applications in production, production scheduling, project managing and other criteria. This issue has been studied since 1960 and is very complicated. In this study, the common presuppositions and limitations regarding such problems will be investigated in addition to their reliability in modelization in order to investigate the possibility of availability of renewable resources using a new attitude. The objective of modelization of RCPSP is quantification of total costs and minimization of delays in projects. Therefore, in order to mathematically modelize RCPSP, non-linear complex integer math programming which transforms into a linear programming model using the features of exponential functions is used. In order to solve the final linear math problem, some experimental examples will be designed in different dimensions, so that the performance and efficiency of the designed model are studied. For solving problems with low dimensions , the Epsilon Constraint multi-objective optimization method is used in an exact optimization software like Lingo. In order to find out the solutions of the ones whose dimensions are high, which exact methods can not solve,the meta-heuristic algorithm called NSGA-II which is a strong one to optimize multi objective problems is used. The results of using these algorithms and the statistical analysis which shows their reliability as 95 percent , indicates that the performance is suitable for genetic algorithms. Therefore this meta-heuristic algorithm has more efficiency and more apposite performance for the recommended model compared with the software of exact optimization. Using the designed math model ,this study can result in decreasing the times of delay in projects and the costs in the scheduling problem and also increasing the reliability when activities are multi-mode.
Research Paper
Supply chain management
davod Andalib Ardakani; Mehrdad Kiani; Ali saffari darberazi; Fatemeh Zamzam; Elham Mofatehzadeh
Abstract
The purpose of this study was to design a model for identifying and ranking the factors influencing green supply chain management in the tile and ceramic industry, which is a significant industry in Iran. The study consisted of three main stages.In the first stage, a systematic review of the literature ...
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The purpose of this study was to design a model for identifying and ranking the factors influencing green supply chain management in the tile and ceramic industry, which is a significant industry in Iran. The study consisted of three main stages.In the first stage, a systematic review of the literature and the Meta-synthesis method were employed to identify and categorize the factors that contribute to the success of green supply chain management. In the second stage, The factors were thoroughly examined and refined through the content validity method. As a result of these steps, a comprehensive model was developed, comprising 30 factors categorized into six dimensions: green suppliers, green technology and expertise, green human resources, green products, Green Organization and Communications, and Green regulations and Support. In the third stage, the Interval Type-2 Fuzzy Analytic Hierarchy Process (IT2FS-AHP) method was utilized to rank the dimensions and factors. Experts' opinions were gathered through a questionnaire to determine the importance of each dimension and factor. The results indicated that the dimensions of green technology and expertise, as well as Green regulations and Support, were deemed the most critical. Furthermore, factors such as "Attention to social responsibility in the organization," "Design and development of evaluation and selection systems of suppliers based on environmental criteria," and "support of operational, middle, and senior managers in implementing the green supply chain" were identified as highly influential in the success of green supply chain management. Overall, the identification and ranking of key factors in green supply chain management contribute to mitigating the adverse environmental impact of industrial activities and enhancing customer satisfaction.
Research Paper
Clustering
Mehdi Ajalli
Abstract
Classification is one of the important tasks in any work and field. Cluster analysis (CA) is one of the most important classification methods. CA is one of the widely used methods in many scientific fields. Clustering is one of the most popular data mining techniques with many applications in industry. ...
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Classification is one of the important tasks in any work and field. Cluster analysis (CA) is one of the most important classification methods. CA is one of the widely used methods in many scientific fields. Clustering is one of the most popular data mining techniques with many applications in industry. Especially, in the field of human resources management, the use of predefined rules is used to determine the performance and division of employees. The main goal of the current research is to design a suitable model for allocating rewards to employees by using the combined approach of the Group Analytical Hierarchy Process (GAHP) and CA. The research method is practical in terms of purpose and descriptive-survey in terms of data collection. For this purpose, first, by designing and distributing a comparative questionnaire of indicators and completing them by the experts of Shahid Fakuri Industries' component manufacturing unit, and by using the group hierarchical analysis process model with Expert Choice software, the weight of the effective indicators in employee evaluation was calculated, then the values of the indicators for 29 employees with using the formula of the normalization function in the Excel software, it is standardized and the weight of the indicators is multiplied by the standard values of the data, and then the distance matrix and the optimal number of clusters are calculated through the Machaon software, and finally, using the discriminative clustering approach and using the K-means method, data clustering was done with SPSS and Makaon software and a suitable model was presented for allocating rewards to the workers of the parts making unit.
Research Paper
Supply chain management
Razieh keshavarzfard; Azam Naderi
Abstract
Approaches to the Vehicle Routing Problem (VRP) have been considered as a practical solution against increasing transportation costs in businesses. In fact, we seek to develop new methods to reduce shipping costs and at the same time maximize profits. Transportation of hazardous materials(HazMat), as ...
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Approaches to the Vehicle Routing Problem (VRP) have been considered as a practical solution against increasing transportation costs in businesses. In fact, we seek to develop new methods to reduce shipping costs and at the same time maximize profits. Transportation of hazardous materials(HazMat), as one of the most complex types of transportation, has always been studied and investigated by researchers. Designers of hazardous materials logistics networks should always design the routes between the hazardous materials’ production center and each of their collection centers, while considering the restrictions related to time windows and uncertainties related to them. In addition, they should take into account vehicle capacity and mileage capacity in sub-tours to minimize total transition and pollution costs. In this research a mathematical model is presented for vehicle routing of hazardous materials, simultaneously from three perspectives (economic, sensitivity of the route and the factors which cause uncertainty in the collection and delivery of hazardous materials). Afterwards, the hybrid Genetic and Simulated Annealing algorithm is applied as an optimization method to solve the problem. Finally, several numerical examples, as well as sensitivity analysis are provided to show the efficiency of the model. The results show as the route sensitivity coefficient increases, the objective function increases. The effect of demand on the objective function is generally upward, but in some cases it is downward.
Research Paper
Reliability and Quality Engineering
Majeed Heydari; Amir Yousefli
Abstract
Offering Maintenance Service Contracts (MSCs) for production equipment can be a good source of revenue for theproviders of these services. To do this, designing an optimal MSCwith a minimum price will be of great interest to service providers. In this paper, for a given equipment item, the effect of ...
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Offering Maintenance Service Contracts (MSCs) for production equipment can be a good source of revenue for theproviders of these services. To do this, designing an optimal MSCwith a minimum price will be of great interest to service providers. In this paper, for a given equipment item, the effect of conducting periodic preventive maintenance on the failure process of the equipment and its corresponding cost is studied. Assuming minimal repair at failure with a random repair cost, the expected cost of maintenance service is estimated. Due to the time delay between selling the contract and paying the repair bills, the time value of service cost at the time of selling the contract is derived. Then, the cost-plus approach is used to determine the price of the MSC. In the presented model, the service provider determines the number of preventive maintenance and the improvement level to minimize the expected price of the MSC. A numerical example with comprehensive sensitivity analysis is presented to illustrate the model and its parameters’ effect. The result shows that the presented model helps the service provider to design a MSC with a minimum price while assuring the profit margin.
Review Paper
Forecasting, production planning, and control
Joyeshree Biswas
Abstract
This study explores the benefits of Total Productive Maintenance (TPM) with a focus on Overall Equipment Effectiveness (OEE) in a Jordanian steel company, investigating the "big six losses" in quality, availability, and speed across industries. A detailed ten-day case study from a Bangladeshi ...
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This study explores the benefits of Total Productive Maintenance (TPM) with a focus on Overall Equipment Effectiveness (OEE) in a Jordanian steel company, investigating the "big six losses" in quality, availability, and speed across industries. A detailed ten-day case study from a Bangladeshi electronics industry highlights collaborative efforts among departments to break down silos and enhance maintenance processes. Engaging frontline workers in daily maintenance activities resulted in notable achievements: 99% in quality, 49% in availability, and 84% in performance scores. The paper recommends strategies such as Single Minute Exchange of Die (SMED), Computer Maintenance Management System (CMMS), and optimized production planning to elevate maintenance procedures and overall productivity within the industry. The findings underscore the critical role of TPM and collaborative efforts in improving maintenance effectiveness and operational efficiency, providing valuable insights for industries seeking to enhance their maintenance processes and achieve higher OEE. Our Research will evaluate this crucial topic for Industrial Application.
Research Paper
Machine Learning
Asude Demir; Seher ARSLANKAYA
Abstract
Autism spectrum disorder affects the whole life of children and leads their families to seek effective treatment and education. According to the Centres for Disease Control and Prevention, the disorder affects one in every 36 children today. Diagnosing this disease at an early age facilitates the treatment ...
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Autism spectrum disorder affects the whole life of children and leads their families to seek effective treatment and education. According to the Centres for Disease Control and Prevention, the disorder affects one in every 36 children today. Diagnosing this disease at an early age facilitates the treatment process and enables children to be reintegrated into society. The use of artificial neural networks, one of the artificial intelligence methods used for prediction, has increased in the field of health in recent years and has become an important tool for early disease diagnosis. In this study, single layer perceptron neural networks were designed for the diagnosis of autism spectrum disorder. Data of 14 different parameters taken from children between 12-36 months of age were used, and as a result of the classification, the accuracy value of the neural network was 99.18%, the sensitivity value was 98.91%, the sensitivity value was 1 and the f1 score value was 99.45%. As a result, it is seen that the perceptron classification algorithm has a very high performance in terms of accuracy, precision, sensitivity and f1 score and successfully discriminates the data
Research Paper
Decision analysis and methods
Ali Sorourkhah
Abstract
Strategic decision-making is often complex and uncertain, especially in turbulent environments. A large number of frequently conflicting indicators, rapid and unpredictable environmental changes, and the long-term consequences of making a decision have revealed the need for managers to use more efficient ...
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Strategic decision-making is often complex and uncertain, especially in turbulent environments. A large number of frequently conflicting indicators, rapid and unpredictable environmental changes, and the long-term consequences of making a decision have revealed the need for managers to use more efficient tools. Today, for tomorrow, conventional tools such as QSPM and MADM help us make the best decision based on yesterday's information. In some scenario planning approaches, the number of scenarios is so few that it cannot represent future uncertainty. In MADM methods, the problem of calculation complexity arises due to the increase in the number of elements. To address these issues, this research proposed an alternative approach for choosing the best strategy in which the alternative strategies are defined by SWOT analysis, future scenarios are determined by applying a matrix approach, irrational scenarios are eliminated by using interpretive structural modelling, and strategies are assessed by implementing robustness analysis. The proposed method involves a case study related to a distributing centre for a food and beverage company located west of Mazandaran province, Iran. Nine alternative strategies' performances were evaluated in twenty-two scenarios based on six significant indicators shaping the future environment, and the best strategy was selected. Finally, some directions for future studies were presented. This study provides managerial implications by showing that despite the classic strategy selection approach being appropriate for austere environments and the MADM models being reasonable for complex environments, robustness analysis produces more reliable results when dealing with turbulent environments.