Analysis of production and service systems under price-dependent intermittent demand

This thesis investigates an all-or-nothing inventory and pricing problem, considering price-dependent and price and yield-dependent intermittent demand scenarios faced by a retailer. The study aims to determine the existence of a threshold policy, optimizing ordering decision and pricing strategies to maximize profit. In price-dependent intermittent demand, we explore a simple demand occurrence probability function of price with various demand size distributions. The focus is on the lost sales model due to its tractability in proving the threshold policy. In addition to the single period, a dynamic programming model for a two-period scenario is developed. Numerical analyses confirm the existence of a threshold policy, with observations indicating sensitivity to holding and unit variable costs. The thesis extends the model to incorporate yield uncertainty, introducing random yield realization and modifying the demand occurrence probability function accordingly. Responsive and unresponsive pricing schemes are explored for both single and two-period, and numerical analyses reveal threshold policies under both schemes. When the expected profit is compared, responsive pricing performs better than unresponsive pricing. This research contributes insights into the interplay of pricing, inventory, and uncertainty, providing practical applications for retail decision-making.