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Non-stationary stochastic inventory lot-sizing with emission and service level constraints in a carbon cap-and-trade system

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journal contribution
posted on 08.11.2016 by Arun Kr. Purohit, Ravi Shankar, Prasanta Kumar Dey, Alok Choudhary
Firms worldwide are taking major initiatives to reduce the carbon footprint of their supply chains in response to the growing governmental and consumer pressures. In real life, these supply chains face stochastic and non-stationary demand but most of the studies on inventory lot-sizing problem with emission concerns consider deterministic demand. In this paper, we study the inventory lot-sizing problem under non-stationary stochastic demand condition with emission and cycle service level constraints considering carbon cap-and-trade regulatory mechanism. Using a mixed integer linear programming model, this paper aims to investigate the effects of emission parameters, product- and system-related features on the supply chain performance through extensive computational experiments to cover general type business settings and not a specific scenario. Results show that cycle service level and demand coefficient of variation have significant impacts on total cost and emission irrespective of level of demand variability while the impact of product’s demand pattern is significant only at lower level of demand variability. Finally, results also show that increasing value of carbon price reduces total cost, total emission and total inventory and the scope of emission reduction by increasing carbon price is greater at higher levels of cycle service level and demand coefficient of variation.The analysis of results helps supply chain managers to take right decision in different demand and service level situations.



  • Business and Economics


  • Business

Published in

Journal of Cleaner Production




654 - 661


PUROHIT, A.K. ... et al., 2016. Non-stationary stochastic inventory lot-sizing with emission and service level constraints in a carbon cap-and-trade system. Journal of Cleaner Production, 113, pp. 654-661.


© Elsevier


AM (Accepted Manuscript)

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This paper was accepted for publication in the journal Journal of Cleaner Production and the definitive published version is available at