Model for Reverse Logistic Problem of Recycling under Stochastic Demand

Beste Desticioglu, Hatice Calipinar, Bahar Ozyoruk and Erdinc Koc
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Beste Desticioglu: Department of Operations Research, Alparslan Defence Science Institute, National Defence University, 06420 Ankara, Turkey
Hatice Calipinar: Department of Business Administration, Faculty of Economics and Administrative Science, Hacettepe University, 06800 Ankara, Turkey
Bahar Ozyoruk: Department of Industrial Engineering, Faculty of Engineering, Gazi University, 06570 Ankara, Turkey
Erdinc Koc: Department of Business Administration, Faculty of Economics and Administrative Science, Bingol University, 12000 Bingol, Turkey

Sustainability, 2022, vol. 14, issue 8, 1-19

Abstract: It has become obligatory for businesses to carry out recycling activities in the face of increasing environmental pollution and the danger of depletion of natural resources. The waste collection phase of the recycling process requires interactive transportation that uses a reverse logistics flow from customers to recycling facilities. Businesses need to create appropriate network structures to carry out these activities at minimum cost. This study has developed a model, based on reverse logistics, of collecting products from customers and sending them to warehouses and then to recycling facilities. The chance-constrained programming (CCP) approach was used to regulate the constraints involving stochastic demand in the model. Linearization was performed using the linear approximation method. The cost of transportation from Initial Collection Points (ICP) warehouses to recycling facilities is the most influential component on the objective function. This linearized model was solved by creating different scenarios by changing the standard deviation ratio, reliability level, and warehouse capacities within the scope of sensitivity analysis. In the sensitivity analysis, it was determined that the increase in confidence level and variance negatively affected the objective function. In addition, it has been concluded that the increase in demand has no effect on costs as long as the capacity of the facility is not exceeded.

Keywords: reverse logistics; recycling; chance-constrained programming; linear approximation method; mathematical model; logistic network (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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