International Journal of Science, Engineering and TechnologyAuthors: Dr. A. Venkateswarlu, Assistant Professor, Kotagiri Rambabu, Assistant professor
Abstract: This paper addresses the joint optimization problem of real-time dynamic pricing and inventory replenishment for perishable goods under stochastic demand and finite shelf life. Traditional economic order quantity (EOQ) models fail to capture time-dependent price elasticity and queuing dynamics at the point of sale. We propose a novel hybrid framework integrating convex optimization (for pricing) with an M/M//1 queuing system (for customer arrival and service). The objective is to maximize the retailer's expected profit over a finite horizon T while minimizing spoilage rate. We derive a closed-form expression for the optimal price p(t) as a function of queue length L(t) and remaining shelf life τ. Using Pontryagin's maximum principle, we prove the existence of a unique optimal control policy. Numerical simulations using real transaction data from a European grocery chain demonstrate a 23.4% improvement in net profit and a 31.2% reduction in spoilage compared to static pricing models. The model achieves ϵ-optimality with convergence in O(1/n) iterations, verified via Monte Carlo cross-validation (99.8% confidence interval).
DOI: http://doi.org/10.5281/zenodo.20583743
