Designing the Reverse Logistics of Newspaper Collection from Household by a Paper Recycling Unit: A Linear Programming Model


  • Vedant Sachin Mamidwar Jain Class of 2023, Daffodil International School, Laxman Nagar, Balewadi, Pune-411045, Maharashtra, India
  • Reetu Jain On My Own Technology Pvt Ltd, Mumbai, India


Reverse logistics, Particle Swarm Optimization, Linear Programming Problem, Newspaper recycling, Transportation cost


In an industry where the logistics is designed to deliver the product to its customers, in a recycling industry it is an assortment of logistics and reverse logistics. It implies that the recycling industry has to design the logistics not only for delivering the products to the customer on time but also for collecting the old or not fit for use products for the purpose of recycling. The logistics of a recycling plant aims at smooth operations of the industry as well as on time delivery of the recycled products to the customers. The comprehensive intention of the present study is to design the reverse logistics of a paper recycling plant in the city of Mumbai. The recycling plant employs daily wagers for a period of 6 hours a day with a remuneration for collecting the unused newspaper from the households. The other costs incurred by the recycling plant is in the form of employing workers, repairing cost, transportation cost and others. The objective of this paper is to optimize the profit of the company by optimizing the cost related to collection of unused newspapers, transportation and number of workers employed. The problem under consideration is represented as a linear programming problem (LPP) and solved using the Particle Swarm Optimization (PSO) algorithm. The optimal value computed by the PSO algorithm is ₹285646. Finally, an in-depth study of the paper recycling industries is also conducted.


Ballou, R. H., & Srivastava, S. K. (2007). Business logistics/supply chain management: planning, organizing, and controlling the supply chain. Pearson Education India.

Irfan, W., Siddiqui, D. A., & Ahmed, W. (2019). Creating and retaining customers: perspective from Pakistani small and medium retail stores. International Journal of Retail & Distribution Management.

Prajapati, H., Kant, R., & Shankar, R. (2019). Bequeath life to death: State-of-art review on reverse logistics. Journal of cleaner production, 211, 503-520.

Dobos, I., & Richter, K. (2004). An extended production/recycling model with stationary demand and return rates. International Journal of Production Economics, 90(3), 311-323.

Ranta, J., Ollus, M., & Leppänen, A. (1992). Information technology and structural change in the paper and pulp industry: Some technological, organizational and managerial implications. Computers in industry, 20(3), 255-269.

Singh, P., & Mishra, R. (2019). Environmental sustainability in libraries through green practices/services. Library Philosophy and Practice, 1-9.

Turki, S., Sauvey, C., & Rezg, N. (2018). Modeling and optimization of a manufacturing/remanufacturing system with storage facility under carbon cap and trade policy. Journal of Cleaner Production, 193, 441-458.

Wilson, D. C., Rodic, L., Modak, P., Soos, R., Carpintero, A., Velis, K., ... & Simonett, O. (2015). Global waste management outlook. UNEP.

Öncel, M. S., Bektaş, N., Bayar, S., Engin, G., Çalışkan, Y., Salar, L., & Yetiş, Ü. (2017). Hazardous wastes and waste generation factors for plastic products manufacturing industries in Turkey. Sustainable environment research, 27(4), 188-194.

Chari, N., Venkatadri, U., & Diallo, C. (2016). Design of a reverse logistics network for recyclable collection in Nova Scotia using compaction trailers. INFOR: Information Systems and Operational Research, 54(1), 1-18.

Valenzuela, J., Alfaro, M., Fuertes, G., Vargas, M., & Sáez-Navarrete, C. (2021). Reverse logistics models for the collection of plastic waste: A literature review. Waste Management & Research, 39(9), 1116-1134.

Vargas, M., Alfaro, M., Karstegl, N., Fuertes, G., Gracia, M. D., Mar-Ortiz, J., ... & Leal, N. (2021). Reverse logistics for solid waste from the construction industry. Advances in Civil Engineering, 2021.

Yu, H., & Solvang, W. D. (2017). A carbon-constrained stochastic optimization model with augmented multi-criteria scenario-based risk-averse solution for reverse logistics network design under uncertainty. Journal of cleaner production, 164, 1248-1267.

Kim, J., Do Chung, B., Kang, Y., & Jeong, B. (2018). Robust optimization model for closed-loop supply chain planning under reverse logistics flow and demand uncertainty. Journal of cleaner production, 196, 1314-1328.

Yan, H., Yu, Z., & Cheng, T. E. (2003). A strategic model for supply chain design with logical constraints: formulation and solution. Computers & Operations Research, 30(14), 2135-2155.

Vahdani, B., Veysmoradi, D., Noori, F., & Mansour, F. (2018). Two-stage multi-objective location-routing-inventory model for humanitarian logistics network design under uncertainty. International journal of disaster risk reduction, 27, 290-306.

Ozgen, D., & Gulsun, B. (2014). Combining possibilistic linear programming and fuzzy AHP for solving the multi-objective capacitated multi-facility location problem. Information Sciences, 268, 185-201.

Yan, H., Yu, Z., & Cheng, T. E. (2003). A strategic model for supply chain design with logical constraints: formulation and solution. Computers & Operations Research, 30(14), 2135-2155.

Cardona-Valdés, Y., Álvarez, A., & Ozdemir, D. (2011). A bi-objective supply chain design problem with uncertainty. Transportation Research Part C: Emerging Technologies, 19(5), 821-832.

Eberhart, R., and Kennedy, J. (1995, October). A new optimizer using particle swarm theory. In MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science (pp. 39-43). IEEE.

Hu, X., Shi, Y., and Eberhart, R. (2004, June). Recent advances in particle swarm. In Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No. 04TH8753) (Vol. 1, pp. 90-97). IEEE.

Malik, R. F., Rahman, T. A., Hashim, S. Z. M., and Ngah, R. (2007). New particle swarm optimizer with sigmoid increasing inertia weight. International Journal of Computer Science and Security, 1(2), 35-44.

Krohling, R. A., Knidel, H., and Shi, Y. (2002). Solving numerical equations of hydraulic problems using particle swarm optimization. In Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No. 02TH8600) (Vol. 2, pp. 1688-1690). IEEE.

Moslehi, G., and Mahnam, M. (2011). A Pareto approach to multi-objective flexible job-shop scheduling problem using particle swarm optimization and local search. International Journal of Production Economics, 129(1), 14-22.




How to Cite

Jain, V. S. M. ., & Jain, R. (2022). Designing the Reverse Logistics of Newspaper Collection from Household by a Paper Recycling Unit: A Linear Programming Model. iJournals:International Journal of Software & Hardware Research in Engineering ISSN:2347-4890, 10(8). Retrieved from

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