Abstract
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).
Highlights
To solve the problem in extensive form, discrete scenarios are generated by moment matching method and the total number of scenarios is reduced by fast forward selection algorithm
Scenario generation and scenario reduction were implemented in GAMS 23.5 to create the most representative scenarios for the stochastic problem
In reverse logistics problem as a supply chain problem, the product flow starts from customers(primary markets) and end at manufacturers(secondary markets)
Summary
The amount of waste generated across the world increases the importance of reverse logistics systems in decreasing waste rate and return the leftover(s) to supply chain. Multi-stage stochastic programming models for reverse logistics problem has not been investigated. To the best of our knowledge, the solution techniques introduced to solve stochastic reverse logistics problems are not efficient to solve largescale instances which include large number of scenarios, stages, and decision variables. Stochasticty of several parameters of the problem along with time horizon complexity, makes multi-stage stochastic programming a good choice as a solution method for the mentioned gaps. This study proposes a multi-stage stochastic program for multi-echelon, multi period reverse logistics program with lot sizing. Sustainability 2021, 13, 13596 distribution of stochastic parameters. Extensive form of problem was used to solve the problem and stochastic solution was evaluated by implementing sensitivity analysis on recursive problem’s parameters
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
