Design and Development of Robust Optimization Model for Sustainable Cross-Docking Systems: A Case Study in Electrical Devices Manufacturing Company

2021 ◽  
pp. 203-224
Author(s):  
Hamdi G. Resat ◽  
Pelin Berten ◽  
Zeliha Kilek ◽  
M. Batuhan Kalay
PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254893
Author(s):  
Juan Feller ◽  
Alejandro F. Mac Cawley ◽  
Jorge A. Ramos-Grez ◽  
Iván La Fé-Perdomo

The acquisition of Advanced Manufacturing Technologies (AMT), such as high-power fiber or CO2 laser cutting equipment, generally involves high investment levels. Its payback period is usually more extended, and there is a moderate-to-high risk involved in adopting these technologies. In this work, we present a robust model that optimizes equipment investing decisions, considers the process’s technical constraint and finds an optimal production plan based on the available machinery. We propose a linear investment model based on historical demand information and take physical process parameters for a LASER cutting equipment, such as cutting speed and gas consumption. The model is then transformed into a robust optimization model which considers demand uncertainty. Second, we determine the optimal production plan based on the results of the robust optimization model and assuming that demand follows a normal distribution. As a case study, we decided on the investment and productive plan for a company that offers Laser-Beam Cutting (LBC) services. The case study validates the effectiveness of the proposed model and proves the robustness of the solution. For this specific application of the model, results showed that the optimal robust solution could increase the company’s expected profits by 6.4%.


Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7456
Author(s):  
Antonio Jiménez-Marín ◽  
Juan Pérez-Ruiz

This paper presents a robust optimization model to find out the day-ahead energy and reserve to be scheduled by an electric vehicle (EV) aggregator. Energy can be purchased from, and injected to, the distribution network, while upward and downward reserves can be also provided by the EV aggregator. Although it is an economically driven model, the focus of this work relies on the actual availability of the scheduled reserves in a future real-time. To this end, two main features stand out: on one hand, the uncertainty regarding the EV driven pattern is modeled through a robust approach and, on the other hand, a set of non-anticipativity constraints are included to prevent from unavailable future states. The proposed model is posed as a mixed-integer robust linear problem in which binary variables are used to consider the charging, discharging or idle status of the EV aggregator. Results over a 24-h case study show the capability of the proposed model.


Author(s):  
Pallavi Dharwada ◽  
Joel S. Greenstein ◽  
Anand K. Gramopadhye ◽  
Steve J. Davis

Author(s):  
Shruti Makarand Kanade

 Cloud computing is the buzz word in today’s Information Technology. It can be used in various fields like banking, health care and education. Some of its major advantages that is pay-per-use and scaling, can be profitably implemented in development of Enterprise Resource Planning or ERP. There are various challenges in implementing an ERP on the cloud. In this paper, we discuss some of them like ERP software architecture by considering a case study of a manufacturing company.


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