Sequencing and scheduling of production in jobshop production systems was investigated in this article. Each operation specific to a job has a random duration with a mean and variance, taking into account this uncertainty in the assumptions of the model, the adaptation More
Sequencing and scheduling of production in jobshop production systems was investigated in this article. Each operation specific to a job has a random duration with a mean and variance, taking into account this uncertainty in the assumptions of the model, the adaptation of the model to the real conditions of the production environment. Each job has the operating costs of the machine during processing, the cost of equipment idle for each unit of time delay in receiving the work. In this study, the optimal scheduling is Reduction of costs. The algorithm used to solve the problem is a genetic algorithm. The efficiency of the proposed algorithms has been tested and analyzed with a number of selected problems from the literature. This study was performed in a situation where the time of operation is uncertain and follows a specific statistical distribution (normal, exponential and uniform). The performance of the genetic algorithm was evaluated based on time criteria and objective function. The results obtained from the genetic algorithm were compared with the results obtained from the combined algorithm (neural network and SA algorithm) and the results obtained from the optimal solving procedures using Lingo software version 6 for 5 sample production scheduling problems. The results show that the integrated algorithm performed better than the genetic algorithm
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Today, the role of industrial clusters as a spatial representation of small and medium industries in providing development in its general sense, both in less developed countries and in more developed countries, is not hidden from anyone because industrial clusters are t More
Today, the role of industrial clusters as a spatial representation of small and medium industries in providing development in its general sense, both in less developed countries and in more developed countries, is not hidden from anyone because industrial clusters are the location of industries. Small and medium appear in relation to each other and together in a geographical context, due to having wide horizontal and vertical links, provide a high level of productivity and efficiency for business formation. The purpose of this study is to prioritize the factors affecting the development of industrial clusters in small and medium industries. The method used in this research is Analytic network process.The statistical population of the present study is the experts of industrial clusters. Finally, spatial factors were in the first place and policy factors were in the second place and economic factors were in the third place finally practical suggestions were provided
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