Fahimeh Tanhaie; Nasim Nahavandi
Abstract
The theory of constraints is an approach to production planning and control that emphasizes on the constraints to increase throughput by effectively managing constraint resources. One application in theory of constraints is product mix decision. Product mix influences the performance measures in multi-product ...
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The theory of constraints is an approach to production planning and control that emphasizes on the constraints to increase throughput by effectively managing constraint resources. One application in theory of constraints is product mix decision. Product mix influences the performance measures in multi-product manufacturing system. This paper presents an alternative approach by using of goal programming to determine the product mix of the manufacturing system. The objective of paper is to provide a methodology in order to make product mix decision. Key point of the proposed methodology is considering decision maker idea to determine the weights of objective functions that are throughput and bottleneck exploitation. Therefore the weights of the objective functions are determined by the information get from decision maker. Through an example, inefficiency of theory of constraints in multiple bottleneck problems has been showed. Comparison of theory of constraints, linear programming and other methods to product mix problem has also discussed to show the advantages of the proposed method.
Hamed Soleimani; Tahere Fattahi Ferdos
Abstract
Today, HSE (health, safety, and environment) systems play a vital role in green and sustainable aspects of the companies. However, performance evaluation of HSE systems is a crucial issue in industry and academia. This paper tries to identify and prioritize the effective factors in HSE performance in ...
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Today, HSE (health, safety, and environment) systems play a vital role in green and sustainable aspects of the companies. However, performance evaluation of HSE systems is a crucial issue in industry and academia. This paper tries to identify and prioritize the effective factors in HSE performance in Iran Khodro (the largest automotive company in Iran) and Tabriz Petrochemical (one of the biggest Iranian petrochemical company). The factors are achieved through the literature and recent publications and then they are customized by the expert's opinions. Finally, a hybrid Fuzzy DEMATEL ANP approach is developed for prioritization of the factors. Indeed, Fuzzy DEMATEL is used in order to determine the relations among factors and sub factors and to help in providing ANP super matrix. Afterward, the Fuzzy ANP is proposed to find the final weights of the factors and sub factors. The weights are used in order to prioritize the factors for two selected companies.
Sajed Rastbin; Farhang Mozaffar; Mostafa Behzadfar; Mehrdad Gholami Shahbandi
Abstract
Motorized transportation systems in the urban areas witnessed huge developments in the infrastructures thanks to the advances in various aspects of technology. This urbanization revolution has its own pros and cons. The resulting dominance of vehicles has limited the presence of people in public places ...
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Motorized transportation systems in the urban areas witnessed huge developments in the infrastructures thanks to the advances in various aspects of technology. This urbanization revolution has its own pros and cons. The resulting dominance of vehicles has limited the presence of people in public places and their participation in social activities, threatening the human based lifestyle of the cities. Historic districts are of most affected areas which withstand the unwanted consequences of such an experience. These areas play a substantial role in urban activities by providing great social activity and walking zones for pedestrians. Hence, in recent years, urban management has paid attention to this endanger regions in order to sustain and enhance their properties by introducing some pedestrianization plan as urban regeneration policies. To design an effective plan, it is necessary to figure out how people behave in response to their environment. Pedestrian modeling is the key to the problem and is studied in the past few decades, mostly in microscopic scale. In addition, a logical decision-making process is required to choose the option with the best outcome in this complex system, considering financial limits of strategic urban planning. In this paper, a macroscopic multi-class user equilibrium pedestrian assignment algorithm is proposed to anticipate the route choice behavior of the pedestrians in a network, and a decision making platform for the pedestrian network design is presented using bi-level mathematical mixed-integer programming and genetic algorithm. The presented model determines the best possible projects to be implemented on the network, considering the constraints of the historic districts. The model brings forward an intelligent framework to help the urban planners in spending the minimum cost, while maximizing some predefined objectives. The proposed method is applied to solve the problem in a test network and in a real case scenario for the historic district of the city of Tehran. The results prove the validity and the efficiency of the algorithm.
Sara Tavassoli; Farnaz Shahpar; Taha-Hossein Hejazi
Abstract
Most of the existing approaches for fuzzy reliability analysis are based on fuzzy probability. The aim of this paper is to describe fuzzy reliability using fuzzy differential equation. The reliability of a system in real world applications is affected by some uncertain parameters. Fuzzy reliability ...
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Most of the existing approaches for fuzzy reliability analysis are based on fuzzy probability. The aim of this paper is to describe fuzzy reliability using fuzzy differential equation. The reliability of a system in real world applications is affected by some uncertain parameters. Fuzzy reliability is a way to present the reliability function uncertainly using fuzzy parameters. In the proposed fuzzy differential equation for reliability, two types of fuzzy derivative: Hukuhara derivative and generalized differentiability are used. It is proved that the Hukuhara differentiability is not adequate for fuzzy reliability analysis. Finally, using the fuzzy integration, the concept of fuzzy mean time to failure (FMTTF) will be introduced. Some numerical simulations are presented to show the applicability and validity of generalized differentiability, in comparison with the Hukuhara differentiability results for fuzzy reliability analysis.
Maryam Shams; Ahmad Jafarzadeh Afshari; Amir Khakbaz
Abstract
Cloud computing is considered to be a new service provider technology for users and businesses. However, the cloud environment is facing a number of challenges. Resource allocation in a way that is optimum for users and cloud providers is difficult because of lack of data sharing between them. On the ...
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Cloud computing is considered to be a new service provider technology for users and businesses. However, the cloud environment is facing a number of challenges. Resource allocation in a way that is optimum for users and cloud providers is difficult because of lack of data sharing between them. On the other hand, job scheduling is a basic issue and at the same time a big challenge in reaching high efficiency in the cloud computing environment. In this paper, “the cloud resources management problem” is investigated that includes allocation and scheduling of computing resources, such that providers achieve the high efficiency of resources and users receive their needed applications in an efficient manner and with minimum cost. For this purpose, a group technology based non-linear mathematical model is presented with an aim at minimization of load difference of servers, number of transfers between servers, number of active virtual machines, maximum construction time, the cost of performing jobs and active servers energy consumption. To solve the model, a meta-heuristic multi-objective hybrid Genetic and Particle Swarm Optimization algorithm is proposed for resource allocation and scheduling. In order to demonstrate the validity and efficiency of the algorithm, a number of problems with different dimensions are randomly created and accordingly the efficiency and convergence capability of the suggested algorithm is investigated. The results indicated that the proposed hybrid method has had an acceptable performance in generating high quality, diverse and sparse solutions.
Mohammad Sadeghi; Parisa Niloofar; Mohsen Ziaee; Zahra Mojaradi
Abstract
One of the key applications of operational research in health systems management is to improve the mechanism of resource allocation and program planning in order to increase the system efficiency. This study seeks to offer an innovative method for the planning and scheduling of health service units with ...
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One of the key applications of operational research in health systems management is to improve the mechanism of resource allocation and program planning in order to increase the system efficiency. This study seeks to offer an innovative method for the planning and scheduling of health service units with the aim of reducing the patients' Length of Stay (LOS) in the Cardiac Surgery Ward of Razavi Hospital of Mashhad. Also, to estimate the patients' LOS, two methods have been applied: multiple One of the key applications of operational research in health systems management is to improve the mechanism of resource allocation and program planning in order to increase the system efficiency. This study seeks to offer an innovative method for the planning and scheduling of health service units with the aim of reducing the patients' Length of Stay (LOS) in the Cardiac Surgery Ward of Razavi Hospital of Mashhad. Also, to estimate the patients' LOS, two methods have been applied: multiple linear regression models and Bayesian networks. The introduced method takes into account all treatment processes of patients in an integrated system and by eliminating any undue waiting time, the length of stay can be reduced to a significant extent. Also, the system efficiency is considerably improved by resolving the current conflicts in the workflow of on-call physicians and optimum allocation of resources, gaining satisfaction of health sector officials and patients. linear regression models and Bayesian networks. The introduced method takes into account all treatment processes of patients in an integrated system and by eliminating any undue waiting time, the length of stay can be reduced to a significant extent. Also, the system efficiency is considerably improved by resolving the current conflicts in the workflow of on-call physicians and optimum allocation of resources, gaining satisfaction of health sector officials and patients.