4.7 Article

Inventory routing model for perishable products toward circular economy

Journal

COMPUTERS & INDUSTRIAL ENGINEERING
Volume 169, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cie.2022.108220

Keywords

Multi-depot; Returnable transport items; closed loop Inventory routing problem; Heterogeneous fleet; Perishable products; CO2 emissions

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This paper introduces an integrated Returnable Transport Items (RTIs) and perishable products closed loop green inventory routing problem with uncertain demand and pickup. The simultaneous delivery of perishable products and pick of empty RTIs and perished products is considered. The proposed comprehensive objective function minimizes the sum of inventory, wastage, routing, and emission costs. The exact solution approach (CPLEX) and meta-heuristic approach (Differential Evolutionary algorithm) are used to solve the proposed model. Numerical results are performed to analyze the benefits of heterogeneous fleet and comprehensive objective functions, as well as sensitivity analysis of various factors.
This paper introduces integrated Returnable Transport Items (RTIs) and perishable products closed loop green inventory routing problem with uncertain demand and pickup. The simultaneously delivery of perishable products and pick of empty RTIs and perished products is considered. A chance constrained programming model for vendor managed inventory system in closed loop supply is modeled. A set of valid inequalities is proposed and their effect on solution time is analyzed. The proposed comprehensive objective function minimizes the sum of inventory, wastage, routing, and emission costs. We have used exact solution approach (CPLEX) and meta-heuristic approach (Differential Evolutionary algorithm) to solve the proposed model. The numerical results are performed to analyze the benefits of heterogeneous fleet and comprehensive objective functions. Further sensitivity analysis is performed to study the effect of unit carbon emission cost, shelf life, demand variability and service level.

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