vibration damping optimization algorithm
در نشریات گروه صنایع-
In the field of scheduling and sequence of operations, one of the common assumptions is the availability of machines and workers on the planning horizon. In the real world, a machine may be temporarily unavailable for a variety of reasons, including maintenance activities, and the full capacity of human resources cannot be used due to their limited number and/or different skill levels. Therefore, this paper examines the Dual Resource Constrained Flexible Job Shop Scheduling Problem (DRCFJSP) considering the limit of preventive maintenance (PM). Due to various variables and constraints, the goal is to minimize the maximum completion time. In this regard, Mixed Integer Linear Programming (MILP) model is presented for the mentioned problem. To evaluate and validate the presented mathematical model, several small and medium-sized problems are randomly generated and solved using CPLEX solver in GAMS software. Because the solving of this problem on a large scale is complex and time-consuming, two metaheuristic algorithms called Genetic Algorithm (GA) and Vibration Damping Optimization Algorithm (VDO) are used. The computational results show that GAMS software can solve small problems in an acceptable time and achieve an accurate answer, and also meta-heuristic algorithms can reach appropriate answers. The efficiency of the two proposed algorithms is also compared in terms of computational time and the value obtained for the objective function.
Keywords: Flexible job-shop scheduling, Dual resource constraint, Preventive maintenance, Genetic algorithm, Vibration damping optimization algorithm -
با پیچیده تر شدن صنایع و افزایش هزینه های تعویض تجهیزات آسیب دیده و تولید، برنامه ریزی تولید و نگهداری و تعمیرات به یکی از مباحث مهم در دنیا تبدیل شده است که با یکپارچه سازی این تصمیمات می توان در جهت کاهش چشم گیر هزینه های تولید گام برداشت. افزایش انتشار گازهای گل خانه یی و آسیب به محیط زیست نیز از جمله دغدغه های این تحقیق است و سعی شده است تا میزان آلاینده های ورودی به صنایع کاهش یابد. این تحقیق به برنامه ریزی توام تولید و نگهداری و تعمیرات می پردازد به گونه یی که برای هر واحد تولیدی سقف مجاز انتشارات کربن مشخص می شود. برای مدیریت منابع، دو نوع راهبرد تولید سبز و عادی مدل سازی و تحلیل شده است. برای دست یابی به بهینگی، با استفاده از دو الگوریتم بهینه سازی مبتنی بر ژنتیک و میرایی ارتعاش بهینه سازی خروجی ها مشخص و کارایی آن ها مقایسه شده است.
کلید واژگان: بهینه سازی توام تولید و نگهداری و تعمیرات، انتشارات کربن، الگوریتم بهینه سازی میرایی ارتعاش، الگوریتم ژنتیکWith increasing the value of optimized production plan and cost of equipment as well as raising the degree of difficulty to change spare parts and equipment, the importance of maintenance planning has doubled. Therefore, we can conclude that nowadays, the necessity of integrating production and maintenance planning is realized for the entire industrial owner and it is going to be the main concern of industrial owners to find the ways which help them optimize their costs. This study presented a new methodology to optimize the production and maintenance planning simultaneously. In terms of the environment, the carbon emission policy was applied. Therefore, the manufacturer should adhere to the emission limitations, which are placed on a company that emits carbon into the environment; otherwise, they should pay penalty. To control the cost of penalty, two types of production strategy including green and regular strategies were applied. In green strategy, the material and fuel were recyclable. Thus, it did less damage to environment but it was more expensive than the regular one. This essay seeks to optimize the amount of production of each strategies by balancing the amount of production with each kind of strategy and we should optimize the cost of production. To formulate the mathematical model, we consider costs of Preventive Maintenances (PMs) and mean of Corrective Maintenance (CM) as objective values to determine the production rate and number of PMs. By using MATLAB program, we could solve the model for two types of algorithm including Genetic and VDO algorithm and compare the solution together. Overall, it was concluded that in small-sized problems, VDO can answer more quickly than GA; yet, they were the same in terms of the solution quality. For some problems, VDO had the best solution, while GA could give the best solution to some other problems. However, overall, their function was somehow equal.
Keywords: Joint optimization of maintenance and production planning, carbon emission, genetic algorithm, vibration damping optimization algorithm
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