Hybrid stochastic and robust optimization model for lot-sizing and scheduling problems under uncertainties

2020 ◽  
Vol 284 (2) ◽  
pp. 485-497 ◽  
Author(s):  
Zhengyang Hu ◽  
Guiping Hu
2009 ◽  
Vol 3 (2) ◽  
pp. 37-48
Author(s):  
Waldemar Kaczmarczyk

This paper presents some important alternatives for modelling Lot-Sizing and Scheduling Problems. First, the accuracy of models can improved by using short time buckets, which allow more detailed planning but lead to higher computational effort. Next, valid inequalities make the models tighter but increase their size. Sometimes it is possible to find a good balance between the size and tightness of a model by limiting a priori the number of valid inequalities. Finally, a special normalization of the variables simplifies the presentation of results and validation of models.


2011 ◽  
Vol 5 (1) ◽  
pp. 49-56
Author(s):  
Waldemar Kaczmarczyk

We consider mixed-integer linear programming (MIP) models of production planning problems known as the small bucket lot-sizing and scheduling problems. We present an application of a class of valid inequalities to the case with lost demand (stock-out) costs. Presented results of numerical experiments made for the the Proportional Lot-sizing and Scheduling Problem (PLSP) confirm benefits of such extended model formulation.


Data in Brief ◽  
2021 ◽  
Vol 35 ◽  
pp. 106810
Author(s):  
Juan Piñeros ◽  
Alyne Toscano ◽  
Deisemara Ferreira ◽  
Reinaldo Morabito

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