Issue: 2025/Vol.35/No.2, Pages
OPTIMIZING PHARMACEUTICAL INVENTORY AND INVESTMENT STRATEGIES DURING PANDEMICS: A DYNAMIC APPROACH INTEGRATING ENVIRONMENTAL EMISSION RATES AND ADVANCED OPTIMIZATION ALGORITHMS
Vinita Dwivedi
, Mamta Keswani , Uttam Kumar Khedlekar , Lalji Kumar
This is not yet the definitive version of the paper. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article.
Cite as: V. Dwivedi, M. Keswani, U. K. Khedlekar, L. Kumar. Optimizing pharmaceutical inventory and investment strategies during pandemics: A dynamic approach integrating environmental emission rates and advanced optimization algorithms. Operations Research and Decisions 2025: 35(2). DOI 10.37190/ord250202
Abstract
This study presents a strategy for managing pharmaceutical inventory during pandemics, focusing on optimizing investment in COVID-19 medicines while ensuring product preservation. A customized inventory model considers critical factors such as price, infection rate, and preservation, adaptable to various pandemic scenarios. Optimal control theory is applied for dynamic investment adjustments, enhancing resource allocations and decision-making. The study addresses a complex replenishment problem involving joint pricing, environmental costs, order costs, preservation technology, and replenishment schedules for non-instantaneous deteriorating items, aiming to maximize retailer's profit. Advanced optimization algorithms, including Ant Colony and Cuckoo Search, determine optimal pricing, investment costs, and replenishment schedules. Theoretical analysis and numerical experiments under a fuzzy learning environment provide a robust foundation for the model. Sensitivity analysis offers practical insights, guiding decision-makers in adapting strategies to real-world challenges. From a managerial perspective, this study provides actionable solutions for balancing profitability with sustainability, ensuring efficient resource use during crises. It also highlights the importance of integrating environmental costs and preservation technology into inventory decisions, particularly in dynamic and uncertain environments like a pandemic. The study delivers comprehensive guidance for effective pandemic response planning, helping managers to make informed decisions that align with both economic and public health goals.
Keywords: Dynamic investment, metaheuristic algorithm, preservation technology, infection awareness investments, fuzzy learning, environment cost, trapezoidal-type demand
Received: 23 March 2024 Accepted: 3 January 2025
Published online: 8 February 2025