A multi-stage stochastic programming model of lot-sizing and scheduling problems with machine eligibilities and sequence-dependent setups

2019 ◽  
Author(s):  
Sheng-I Chen ◽  
Delvinia Su
Keyword(s):  
Stochastic Programming ◽  
Programming Model ◽  
Lot Sizing ◽  
Scheduling Problems ◽  
Sequence Dependent ◽  
Multi Stage ◽  
Stochastic Programming Model ◽  
Lot Sizing And Scheduling

scholarly journals A Multi-Stage Stochastic Programming Model for the Multi-Echelon Multi-Period Reverse Logistics Problem

2021 ◽  
Vol 13 (24) ◽  
pp. 13596
Author(s):  
Vahid Azizi ◽  
Guiping Hu
Keyword(s):  
Reverse Logistics ◽  
Programming Model ◽  
Lot Sizing ◽  
Continuous Distribution ◽  
Optimal Solution ◽  
Forward Selection ◽  
Multi Stage ◽  
Stochastic Parameters ◽  
Stochastic Solution ◽  
Stochastic Programming Model

Reverse logistics planning plays a crucial role in supply chain management. Stochasticity in different parameters along with time horizon can be a challenge in solving reverse logistics problems. This paper proposes a multi-stage, multi-period reverse logistics with lot sizing decisions under uncertainties. The main uncertain factors are return and demand quantities, and return quality. Moment matching method was adopted to generate a discrete set of scenarios to represent the original continuous distribution of stochastic parameters. Fast forward selection algorithm was employed to select the most representative scenarios and facilitate computational tractability. A case study was conducted and optimal solution of the recursive problem obtained by solving extensive form. Sensitivity analysis was implemented on different elements of stochastic solution. Results sow that solution of recursive problem (RP) outperforms the solution obtained from the problem with expected values of uncertain parameters (EEV).

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