scholarly journals A Bender’s Algorithm of Decomposition Used for the Parallel Machine Problem of Robotic Cell

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1730
Author(s):  
Mohammad Reza Komari Alaei ◽  
Mehmet Soysal ◽  
Atabak Elmi ◽  
Audrius Banaitis ◽  
Nerija Banaitiene ◽  
...  

The present research addresses the single transportation robot used to alleviate problems of robotic cell scheduling of the machines. For the purpose of minimizing the make-span, a model of mixed-integer linear programming (MILP) has been suggested. Since the inefficiency exists in NP-hard, a decomposition algorithm posed by Bender was utilized to alleviate the problem in real life situations. The proposed algorithm can be regarded as an efficient attempt to apply optimality Bender’s cuts regarding the problem of parallel machine robotic cell scheduling in order to reach precise resolutions for medium and big sized examples. The numerical analyses have demonstrated the efficiency of the proposed solving approach.

2021 ◽  
Vol 11 (20) ◽  
pp. 9551
Author(s):  
Ali Louati ◽  
Rahma Lahyani ◽  
Abdulaziz Aldaej ◽  
Racem Mellouli ◽  
Muneer Nusir

This paper presents multiple readings to solve a vehicle routing problem with pickup and delivery (VRPPD) based on a real-life case study. Compared to theoretical problems, real-life ones are more difficult to address due to their richness and complexity. To handle multiple points of view in modeling our problem, we developed three different Mixed Integer Linear Programming (MILP) models, where each model covers particular constraints. The suggested models are designed for a mega poultry company in Tunisia, called CHAHIA. Our mission was to develop a prototype for CHAHIA that helps decision-makers find the best path for simultaneously delivering the company’s products and collecting the empty boxes. Based on data provided by CHAHIA, we conducted computational experiments, which have shown interesting and promising results.


Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 887
Author(s):  
Xianliang Cheng ◽  
Suzhen Feng ◽  
Yanxuan Huang ◽  
Jinwen Wang

Peak-shaving is a very efficient and practical strategy for a day-ahead hydropower scheduling in power systems, usually aiming to appropriately schedule hourly (or in less time interval) power generations of individual plants so as to smooth the load curve while enforcing the energy production target of each plant. Nowadays, the power marketization and booming development of renewable energy resources are complicating the constraints and diversifying the objectives, bringing challenges for the peak-shaving method to be more flexible and efficient. Without a pre-set or fixed peak-shaving order of plants, this paper formulates a new peak-shaving model based on the mixed integer linear programming (MILP) to solve the scheduling problem in an optimization way. Compared with the traditional peak-shaving methods that need to determine the order of plants to peak-shave the load curve one by one, the present model has better flexibility as it can handle the plant-based operating zones and prioritize the constraints and objectives more easily. With application to six cascaded hydropower reservoirs on the Lancang River in China, the model is tested efficient and practical in engineering perspective.


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