Modified Reptile Search Optimization Based Analysis of Inventory Framework With Interval-Valued Inventory Expenses

Authors

  • Yogesh Sharma Professor, School of Engineering & Technology, Jaipur National University, Jaipur, india
  • Anurag Kushwaha Assistant Professor, School of Management & Commerce, Dev Bhoomi Uttarakhand University, Uttarakhand, India
  • Manju Bargavi Sankar Krishnamoorthy Professor, Department of Computer Science and IT, Jain(Deemed-to-be University), Bangalore-27, India
  • Priyank Singhal Associate Professor, College of Computing Science and Information Technology, Teerthanker Mahaveer University, Moradabad, Uttar Pradesh, India

Keywords:

Inventory model, advance payment, IV expenses, Modified Reptile Search Optimization (MRSO)

Abstract

This study presents an inventory model that incorporates interval-valued inventory expenses and the effect of pre-payment (PP). The PP is a fixed proportion of the cycle's total procurement expense; this results in a discount on procurement expense but a loss of interest on the PP. It is assumed that the inventory expenses, including ordering, purchase, shortage, and carrying expenses, are interval-valued. We examine two scenarios: one with no shortages and the other allowing for partially backlogged deficiencies. Due to loyal customers and some customers transferring shops, the demand rate is projected to fall over a limited interval in the second case. Both cases use interval arithmetic to design mixed integer restricted optimization issues with interval targets. We proposed a Modified Reptile Search Optimization (MRSO) algorithm to tackle these issues. The suggested model is demonstrated numerically, and sensitivity analysis are carried out to determine the effects of various inventory factors on optimal profit. The inventory model with interval-valued (IV) expenses can be solved most effectively using the MRSO method. The results emphasize PP, IV expenses, and shortage cases in inventory management. The model and MRSO algorithms assist decision-makers in improving their inventory strategies and optimizing profitability under uncertain expense and demand conditions.

Downloads

Download data is not yet available.

References

Muchaendepi, W., Mbohwa, C., Hamandishe, T. and Kanyepe, J., 2019. Inventory management and performance of SMEs in the manufacturing sector of Harare. Procedia Manufacturing, 33, pp.454-461.

Wang, Q., Zhao, N., Wu, J., and Zhu, Q., 2021. Optimal pricing and inventory policies with reference price effect and loss-averse customers. Omega, 99, p.102174.

Wang, J., Qiu, Q. and Wang, H., 2021. Joint optimization of condition-based and age-based replacement policy and inventory policy for a two-unit series system. Reliability Engineering & System Safety, 205, p.107251.

Brunaud, B., Laínez‐Aguirre, J.M., Pinto, J.M. and Grossmann, I.E., 2019. Inventory policies and safety stock optimization for supply chain planning. AIChE journal, 65(1), pp.99-112.

Patoghi, A. and Mousavi, S.M., 2021. A new approach for material ordering and multi-mode resource constraint project scheduling problem in a multi-site context under interval-valued fuzzy uncertainty. Technological Forecasting and Social Change, 173, p.121137.

Ruidas, S., Seikh, M.R., Nayak, P.K. and Tseng, M.L., 2023. An interval-valued green production inventory model under controllable carbon emissions and green subsidy via particle swarm optimization. Soft Computing, pp.1-25.

Foroozesh, N., Karimi, B., Mousavi, S.M. and Mojtahedi, M., 2023. A hybrid decision-making method using robust programming and interval-valued fuzzy sets for sustainable-resilient supply chain network design considering circular economy and technology levels. Journal of Industrial Information Integration, 33, p.100440.

Sun, L., Zhu, L., Li, W., Zhang, C. and Balezentis, T., 2022. Interval-valued functional clustering based on the Wasserstein distance with application to stock data. Information Sciences, 606, pp.910-926.

Sarvestani, S.S. and Reza Davoodi, S.M., 2022. Optimal Daily Scalping Stock Trading Portfolio Based on Interval-Valued Prediction with ANN Approach. Financial Management Perspective/Chashm/&āz-i Mudīriyyat-i Mālī, 12(39).

Ruidas, S., Seikh, M.R. and Nayak, P.K., 2021. A production inventory model with interval-valued carbon emission parameters under price-sensitive demand. Computers & Industrial Engineering, 154, p.107154.

Manna, A.K., Das, S., Shaikh, A.A., Bhunia, A.K. and Moon, I., 2023. Carbon emission controlled investment and warranty policy based production inventory model via meta-heuristic algorithms. Computers & Industrial Engineering, p.109001.

Manna, A.K. and Bhunia, A.K., 2022. Investigation of green production inventory problem with selling price and green level sensitive interval-valued demand via different metaheuristic algorithms. Soft Computing, 26(19), pp.10409-10421.

Shaikh, A.A., Das, S.C., Bhunia, A.K., Panda, G.C. and Al-Amin Khan, M., 2019. A two-warehouse EOQ model with interval-valued inventory expenses and advance payment for deteriorating item under particle swarm optimization. Soft Computing, 23(24), pp.13531-13546.

Ramana, K. V. ., Muralidhar, A. ., Balusa, B. C. ., Bhavsingh, M., & Majeti, S. . (2023). An Approach for Mining Top-k High Utility Item Sets (HUI). International Journal on Recent and Innovation Trends in Computing and Communication, 11(2s), 198–203. https://doi.org/10.17762/ijritcc.v11i2s.6045

Leila Abadi, Amira Khalid, Predictive Maintenance in Renewable Energy Systems using Machine Learning , Machine Learning Applications Conference Proceedings, Vol 3 2023.

Downloads

Published

04.11.2023

How to Cite

Sharma, Y. ., Kushwaha, A. ., Krishnamoorthy, M. B. S. ., & Singhal, P. . (2023). Modified Reptile Search Optimization Based Analysis of Inventory Framework With Interval-Valued Inventory Expenses. International Journal of Intelligent Systems and Applications in Engineering, 12(3s), 334–342. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3712

Issue

Section

Research Article

Similar Articles

You may also start an advanced similarity search for this article.