amirfoad sateie

Due to the importance of manufacturing and production systems issues in modern businesses, in recent years, many magazines and researchers have focused their research on this field. Manufacturing and production is an emerging pattern in which production resources are hardware (handling materials, equipment, tools and machines, computers), software (computer-aided design, computer-aided production) and production capabilities (ability design, production, maintenance, repair, management, simulation, optimization) is virtualized and available to users in the entire manufacturing and production cycle and allows the joint use of production systems and resources produced at the global level. Manufacturing and production based on new technologies is a solution that enables users to receive their requests in different layers with optimal timing. Therefore, the main goal of this research is to provide a mathematical model to optimize the production output function in dynamic manufacturing and production systems. For this purpose, the researcher first conducted a comprehensive and complete study of the research literature, and after collecting the information, he selected and developed the initial model, and in the second phase of the research, he started by obtaining statistical information and data from the relevant statistical community, to build the model. Its original and initial test was done. Since the problem of optimizing the production output function in dynamic manufacturing and production systems is included in the NP-hard category, it means that for such problems, a quick and feasible solution has not been found in a reasonable time from the genetic algorithm and ant colony in MATLAB software was used and through the tools and methods of solving and analyzing them, the questions of the current research were given a suitable and optimal answer.

One of the main problems of the industrial society today is the low quality of products, the failure of products and systems, which causes problems at various levels of production and even causes catastrophic events for society and the environment. Weakness in dynamic manufacturing and production systems and weakness in optimizing these systems is an issue that needs to be addressed. Therefore, the main purpose of the present study is to answer some of these issues and problems in the statistical community. The researcher intends to analyze the issue as the main solution in the optimization of the output function of manufacturing systems. The problem was modeled by considering the constraints and assumptions set as nonlinear integer programming (MINLP). Then, to achieve the optimal global solution, using linearization techniques, the mathematical model of the problem was converted to linear integer linear programming (MILP). Based on this, the target function was examined using the genetic algorithm in MATLAB software and its results were presented for small, medium, and large dimensions for problem factories with different dimensions (sensitivity analysis).