Mahesh Kumar Jayaswal
Department of Applied Science and Humanities, School of Engineering and Sciences, MIT Art, Design and Technology University, 412201, Pune, Maharashtra, India.

Masood Alam
Department of Math & IT, CPS, Sultan Qaboos University, Muscat, Oman.

Khursheed Alam
Department of Mathematics & Data Science, The A. H. Siddiqi Centre for Advanced Research in Applied Mathematics & Physics (CARAMP), Sharda University, 201310, Greater Noida, Uttar Pradesh, India.

Santosh Kumar
Department of Mathematics & Data Science, The A. H. Siddiqi Centre for Advanced Research in Applied Mathematics & Physics (CARAMP), Sharda University, 201310, Greater Noida, Uttar Pradesh, India.

Jai Deep Pandey
Department of Mathematics and Statistics, Banasthali Vidyapith, Tonk, 304022, Rajasthan, India.

DOI https://doi.org/10.33889/IJMEMS.2026.11.5.093

  ;

Abstract

The present paper deals with a fuzzy-based supply chain model with the effect of learning for the supply chain under queuing theory, where carbon emission policies are allowed. Nowadays, carbon emissions affect the environment and ordering policies of industries. It is considered that storage items emit carbon units, and the carbon emission cost is included in this paper. The effect of learning reduces the total fuzzy cost per shipment during ordering policies, and the backordering cost and setup expenses follow the effect of learning, where the holding cost has been taken as fuzzy input parameters. The queuing concept is included in this model, and the proposed model is classified into three models under the learning effect. The manufacturer produces multiple items due to the multiple demands of the products from several buyers, and the produced items are stored in different warehouses. The total fuzzy cost is defuzzified with the help of the graded mean integration method under the proposed scenario, and the total cost function is compared with and without a fuzzy environment under the learning effect. For the justification of the proposed model, numerical examples have been presented, and a sensitivity analysis has also been presented to know about the changeable effect of inventory parameters that are involved in this model.

Keywords- Learning effect, Carbon emission, Fuzzy environment, Multiproduct, Supply chain.

Citation

Jayaswal, M. K. Alam, M., Alam, K., Kumar, S., & Pandey, J. D. (2026). A Multi Objective Sustainable Queuing Supply Chain Model with Learning Effects and Fuzzy Environment. International Journal of Mathematical, Engineering and Management Sciences, 11(5), 2318-2339. https://doi.org/10.33889/IJMEMS.2026.11.5.093.