در هنگام جستجو کلمه در قسمت عنوان میتوانید کلمات مورد جستجو را با کاراکتر (-) جدا کنید.

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- و: تمام کلمات انتخابی را در عنوان مقاله یا کتاب نیاز دارید
- یا: یعنی یکی از کلمات نیز داخل عنوان باشد کافی است

- جایگاه : پژوهشی
- مجله: Journal of Modern Processes in Manufacturing and Production
- نوع مقاله: Journal Article
- کلمات کلیدی: Multi-Product,Production Lot Size,Continuous Time,One Machine
- چکیده:
- چکیده انگلیسی: In this research, the production of multi-products using one machine is investigated in continuous time. The machine has limited capacity and can produce only one product at any time. To change the product, the machine should be set up. Due to the difference in demand for products, there is no need to equate the number of machine start-ups for these products, by removing this constraint, a nonlinear mathematical model is presented that gives the optimal production lot size for each product. To solve the single-constraint nonlinear model, the Lagrange method is used. For a numerical example, the obtained solution is compared with the method of rotating a constant cycle. Due to the total cost, the solution was better than the solution of the rotation cycle method. Also, contrary to the rotation cycle method, the total holding cost is equal to the total setup costs, which is similar to the Wilson inventory basic formula.
- انتشار مقاله: 26-09-1398
- نویسندگان: Ayub Rahimzadeh,Ayub Rahimzadeh,Ayub Rahimzadeh
- مشاهده

- جایگاه : پژوهشی
- مجله: Journal of Modern Processes in Manufacturing and Production
- نوع مقاله: Journal Article
- کلمات کلیدی: Artificial Neural Network,Supply Chain,Discrete Wavelet transform,Bullwhip Effect,demand
- چکیده:
- چکیده انگلیسی: In this paper, we present a new predictive hybrid model using discrete wavelet transform (DWT), and the artificial neural network (ANN) to reduce the bullwhip effect of demand in supply chain to obtain a real amount of final customer demand. Also, we compare our result with more comprehensive sample of previous research to extend the scope of our study. In this new research our methodology is combine two discrete wavelet transform (DWT), and the artificial neural network (ANN) was used to analyze the data. Results indicated that in comparison with the previous methods of prediction to reduce the bullwhip effect in supply chains, the use of DWT and ANN is more favorable leading to less error against other methods. Moreover, we discrete our data in liner data and nonlinear data because since the combinational method uses nonlinear data and gives importance to these data rather than linear data, it can be concluded that in comparison with linear data, nonlinear data have more importance in predicting the bullwhip effect. According to this new combinational technique, organizations can obtain suitable amounts of demand at all stages of supply chain, which makes a low distance between true and forecasting demands. Therefore, organizations can avoid some costs that playing an inessential role in their products.
- انتشار مقاله: 18-02-1398
- نویسندگان: Afshin Yousefi,Ayub Rahimzadeh,Alireza Moradi
- مشاهده

- جایگاه : پژوهشی
- مجله: Advances in Mathematical Finance and Application
- نوع مقاله: Journal Article
- کلمات کلیدی: Closed loop supply chain Unreliability,Multi-objective planning,NSGA-II algorithm
- چکیده:
- چکیده انگلیسی: In the current world, the debate on the reinstatement and reuse of consumer prod-ucts has become particularly important. Since the supply chain of the closed loop is not only a forward flow but also a reverse one; therefore, companies creating integ-rity between direct and reverse supply chain are successful. The purpose of this study is to develop a new mathematical model for closed loop supply chain net-work. In the real world the demand and the maximum capacity offered by the sup-plier are uncertain which in this model; the fuzzy theory discussion was used to cover the uncertainty of the mentioned variables. The objective functions of the model include minimizing costs, increasing revenues of recycling products, increas-ing cost saving from recycling and environmental impacts. According to the NP-hard, an efficient algorithm was suggested based on the genetic Meta heuristic algo-rithm to solve it. Twelve numerical problems were defined and solved using the NSGA-II algorithm to validate the model
- انتشار مقاله: 18-12-1397
- نویسندگان: Sadegh Feizollahi,Heresh Soltanpanah,Ayub Rahimzadeh
- مشاهده

- جایگاه : پژوهشی
- مجله: Advances in Mathematical Finance and Application
- نوع مقاله: Journal Article
- کلمات کلیدی: Cost,environmental risks,Project quality,Generalized pre-requisites,Bee Colony algorithm
- چکیده:
- چکیده انگلیسی: Today, in large projects such as constructing oil, gas and petrochemical refineries, it is inevitable to use modern management methods and project timing. On the other hand, in classic scheduling case, the focus is on balance between time and cost of carrying out projects, which in such a situation, one of possible solutions to shorten time of implementing project is to accelerate activities. This acceleration can affect the quality of conducting projects and environmental impacts, in addition to impose more costs. Hence, in such studies, environmental impacts and quality of activities were also considered as new indicators in case of project time-cost balance. There has been proposed a new mathematical model with four indicators: cost, time, quali-ty and environmental impacts. The provided model is a multi-objective mathematical model of zero-and-one programming type that despite traditional models, in which there is only considered an implementation mode for carrying out activities and a pre-conditional relationship between activities, modes of implementing activities are as multi-form and the dependence relationship between the activities is a generalized pre-requisite. Including the relationships brings the problem closer to the real world. Because of NP-hard of the problem in large dimensions and the necessity of using meta-heuristic Algorithms, we used MOBEE algorithm to solve the model.
- انتشار مقاله: 18-12-1397
- نویسندگان: Hossein Ali Heydari,Heresh Soltanpanah,Ayub Rahimzadeh
- مشاهده