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EPOIM: an advanced optimization method for two warehouse inventory model

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Abstract

Due to the uncertain fluctuations in a competitive business, storage costs are always unstable. The inventory design of an item is established in a stochastic situation with cost-based demand over a fixed time horizon. Order placement is linked with an advanced payment system in any business. Most existing inventory models are developed only by focusing on a single objective, which results in inaccurate sensitivity. To overcome such issues, this work focused on multiple objectives like total cost optimization, advanced payment, partial backlogging and cost-based demand with the help of the Emperor Penguin Optimization (EPO) algorithm. The Emperor Penguin Optimized Inventory Model (EPOIM) is proposed for the inventory management of two warehouse models. The two warehouses are developed with fixed capacity, and the corresponding inventory management is optimized based on the multiple defined objectives. Also, the proposed model can be extended in numerous ways. For example, it may extend the constant demand to a more generalized demand pattern that fluctuates with time. Also, it could consider the unit purchase cost, the inventory holding cost, and others, which also fluctuate with time. For result validation purposes, a Matlab environment is used. Parameters like sensitivity, optimum cost, algorithm convergence and statistical analysis are evaluated and compared with existing methods such as Constriction Coefficient-based Particle Swarm Optimization (PSO-CO), Weighted Quantity based PSO (WQPSO) and Genetic Quantity based PSO (GQPSO). When compared to existing methods, the proposed model obtains 3225.753256 as the average cost, which is 0.156% less than PSO-CO and GQPSO, as well as 0.157% less than WQPSO methods.

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References

  1. Jaggi CK, Cárdenas-Barrón LE, Tiwari S, Shafi A (2017) Two-warehouse inventory model for deteriorating items with imperfect quality under the conditions of permissible delay in payments. ScientiaIranica 24(1):390–412

    Google Scholar 

  2. Alamri AA, Syntetos AA (2018) Beyond LIFO and FIFO: exploring an Allocation-In-Fraction-Out (AIFO) policy in a two-warehouse inventory model. Int J Prod Econ 206:33–45

    Article  Google Scholar 

  3. Tiwari S, Jaggi CK, Bhunia AK, Shaikh AA, Goh M (2017) Two-warehouse inventory model for non-instantaneous deteriorating items with stock-dependent demand and inflation using particle swarm optimization. Ann Oper Res 254(1–2):401–423

    Article  MathSciNet  Google Scholar 

  4. Chakraborty D, Jana DK, Roy TK (2018) Two-warehouse partial backlogging inventory model with ramp type demand rate, three-parameter Weibull distribution deterioration under inflation and permissible delay in payments. Comput Ind Eng 123:157–179

    Article  Google Scholar 

  5. Yadav AS, Tyagi B, Sharma S, Swami A (2017) Effect of inflation on a two-warehouse inventory model for deteriorating items with time varying demand and shortages. Int J Procure Manag 10(6):761–775

    Google Scholar 

  6. Shaikh AA (2017) A two warehouse inventory model for deteriorating items with variable demand under alternative trade credit policy. Int J Logist Syst Manag 27(1):40–61

    Google Scholar 

  7. Yadav AS, Swami A, Kher G (2017) Soft computing optimization of two warehouse inventory model with genetic algorithm. Asian J Math Comput Res 19(4):214–23

  8. Zikria YB, Afzal MK, Kim SW (2020) Internet of multimedia things (IoMT): Opportunities, challenges and solutions. Sensors 20(8):2334

    Article  Google Scholar 

  9. Chandra S (2020) Two warehouse inventory model for deteriorating items with stock dependent demand under permissible delay in payment. J Math Comput Sci 10(4):1131–1149

    Google Scholar 

  10. Berthiaume A, Arnot JA, Toose L (2022) Risk-based prioritization of organic substances in the Canadian National Pollutant Release Inventory using an evaluative regional-scale multimedia mass balance model. Integr Environ Assess Manag 18(6):1722–1732

    Article  Google Scholar 

  11. Yadav AS, Swami A, Kher G (2018) Particle swarm optimization of inventory model with two warehouses. Asian J Math Comput Res 23(1):17–26

  12. Kaliraman NK, Raj R, Chandra S, Chaudhary H (2017) Two warehouse inventory model for deteriorating item with exponential demand rate and permissible delay in payment. Yugoslav J Oper Res 27(1):109–124

    Article  MathSciNet  Google Scholar 

  13. Waliv RH, Umap HP (2018) Multi item two-warehouse fuzzy inventory model. Int J Procure Manag 11(4):443–454

    Google Scholar 

  14. Palanivel M, Priyan S, Mala P (2018) Two-warehouse system for non-instantaneous deterioration products with promotional effort and inflation over a finite time horizon. J Ind Eng Int 14(3):603–612

    Article  Google Scholar 

  15. Yadav AS, Swami A, Kumar S (2018) An inventory model for deteriorating items with two warehouses and variable holding cost. Int J Pure Appl Math 120(6):3069–3086

    Google Scholar 

  16. Yadav AS, Swami A, Kumar S (2018) A supply chain inventory model for decaying items with two ware-house and partial ordering under inflation. Int J Pure Appl Math 120(6):3053–3068

    Google Scholar 

  17. Malik AK, Chakraborty D, Bansal KK, Kumar S (2017) Inventory model with quadratic demand under the two warehouse management system. Int J Eng Technol (IJET) 3(3):2299–2303

    Google Scholar 

  18. Lin YS, Wang KJ (2018) A two-stage stochastic optimization model for warehouse configuration and inventory policy of deteriorating items. Comput Ind Eng 120:83–93

    Article  Google Scholar 

  19. Hemasian-Etefagh F, Safi-Esfahani F (2020) Group-based whale optimization algorithm. Soft Comput 24(5):3647–3673

    Article  Google Scholar 

  20. Mahafzah BA, Jabri R, Murad O (2021) Multithreaded scheduling for program segments based on chemical reaction optimizer. Soft Comput 25(4):2741–2766

    Article  Google Scholar 

  21. Al-Shaikh A, Mahafzah BA, Alshraideh M (2021) Hybrid harmony search algorithm for social network contact tracing of COVID-19. Soft Comput 28:1–23

    Google Scholar 

  22. Al-Shaikh A, Mahafzah BA, Alshraideh M (2019) Metaheuristic approach using grey wolf optimizer for finding strongly connected components in digraphs. J Theor Appl Inf Technol 97:4439–4452

    Google Scholar 

  23. Masadeh R, Alsharman N, Sharieh A, Mahafzah BA, Abdulrahman A (2021) Task scheduling on cloud computing based on sea lion optimization algorithm. Int J Web Inf Syst 17(2):99–116

    Article  Google Scholar 

  24. Dutta P, Choudhury PD (2015) A fuzzy based two warehouse inventory model for deteriorating items with cubic demand and different fuzzy cost parameters. Int J Eng Res Gen Sci 3(5):209–218

    Google Scholar 

  25. Deb M, Kaur P, Sarma KK (2019) Fuzzy approach to decision support system design for inventory control and management. J Intell Syst 28(4):549–557

    Google Scholar 

  26. Malik AK, Singh Y, Gupta SK (2012) A fuzzy based two warehouses inventory model for deteriorating items. Int J Soft Comput Eng 2(2):188–192

    Google Scholar 

  27. Roy SK, Pervin M, Weber GW (2020) A two-warehouse probabilistic model with price discount on backorders under two levels of trade-credit policy. J Ind Manag Optim 16(2):553

    Article  MathSciNet  Google Scholar 

  28. Saxena P, Singh C, Sharma K (2020) Green design and product stewardship approach for two-warehouse inventory model. Indian J Sci Technol 13(37):3850–3870

    Article  Google Scholar 

  29. Harit A, Sharma A, Singh S (2020) Effect of preservation technology on optimization of two warehouse inventory model for deteriorating items. In: Decision Analytics Applications in Industry. Springer, Singapore, pp 431–442

  30. Sahoo CK, Paul KC, Kumar S (2020) Two warehouses EOQ inventory model of degrading matter having exponential decreasing order, limited suspension in price including salvage value. SN Comput Sci 1(6):1–9

    Article  Google Scholar 

  31. Shaikh AA, Das SC, Bhunia AK, Panda GC, Khan MAA (2019) A two-warehouse EOQ model with interval-valued inventory cost and advance payment for deteriorating item under particle swarm optimization. Soft Comput 23(24):13531–13546

    Article  Google Scholar 

  32. Mashud AH, Wee HM, Sarkar B, Li YH (2020) A sustainable inventory system with the advanced payment policy and trade-credit strategy for a two-warehouse inventory system. Kybernetes 50(5):1321–1348

  33. Das SC, Manna AK, Rahman MS, Shaikh AA, Bhunia AK (2021) An inventory model for non-instantaneous deteriorating items with preservation technology and multiple credit periods-based trade credit financing via particle swarm optimization. Soft Comput 25(7):5365–5384

    Article  Google Scholar 

  34. Rahman MS, Duary A, Shaikh AA, Bhunia AK (2022) An application of real coded self-organizing migrating genetic algorithm on a two-warehouse inventory problem with Type-2 interval valued inventory costs via mean bounds optimization technique. Appl Soft Comput 124:109085

    Article  Google Scholar 

  35. Manna AK, Akhtar M, Shaikh AA, Bhunia AK (2021) Optimization of a deteriorated two-warehouse inventory problem with all-unit discount and shortages via tournament differential evolution. Appl Soft Comput 107:107388

    Article  Google Scholar 

  36. Bhunia AK, Shaikh AA (2016) Investigation of two-warehouse inventory problems in interval environment under inflation via particle swarm optimization. Math Comput Model Dyn Syst 22(2):160–179

    Article  MathSciNet  Google Scholar 

  37. Sun J, Xu W, Feng B (2004) A global search strategy of quantum-behaved particle swarm optimization. IEEE Conf Cybern Intell Syst 1:111–116

    Google Scholar 

  38. Dhiman G, Kumar V (2018) Emperor penguin optimizer: a bio-inspired algorithm for engineering problems. Knowl-Based Syst 159:20–50

    Article  Google Scholar 

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  1. SRM Institute of Science and Technology, Delhi NCR Campus, Modinagar, Uttar Pradesh, 201204, India

    Sunil Kumar & Rajendra Prasad Mahapatra

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  1. Sunil Kumar
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  2. Rajendra Prasad Mahapatra
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Correspondence to Sunil Kumar.

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Kumar, S., Mahapatra, R.P. EPOIM: an advanced optimization method for two warehouse inventory model. Multimed Tools Appl (2024). https://doi.org/10.1007/s11042-024-19064-4

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