Narrow Results

According to the marketing principle, a decision maker may control demand rate through selling price and the unit facility cost of promoting transaction. In fact, the upper bound of willing-to-pay price and the transaction cost probably depend upon the subjective judgment of individual consumer in purchasing merchandise. This study therefore attempts to construct a bivariate distribution function to simultaneously incorporate the willing-to-pay price and the transaction cost into the classical economic order quantity (EOQ) model. Through the manipulation of the constructed bivariate distribution function, the demand function faced by the supplier can be expressed as a concrete form. The proposed mathematical model mainly concerns how to determine the initial inventory level for each business cycle, so that the profit per unit time is maximized by means of the selling price and the unit-transaction cost to control the selling rate. Furthermore, the sensitivity analysis of optimal solution is performed and the implication of this extended inventory model is also discussed.

We consider the extended economic production quantity (EPQ) problem when demand follows a Poisson process in a production system. A fixed lot sizing policy is implemented to minimize fluctuation of workload, and to smooth production planning and inventory control. The considered costs include setup cost, inventory carrying cost, and shortage cost when demand cannot be satisfied from stock. The main contributions of this paper are two folds. We develop and analyze the extended EPQ model. Under some mild conditions, the expected cost per unit time can be shown to be convex. Via computational experiments, we demonstrate that, in comparison with classical EPQ model, the average reduction of expected cost is significant when demand is random and the proposed model is used to determine lot sizing policy. Our computational tests have also illustrated the impact of various parameters on the expected cost model and the lot sizing policy.

A model is constructed for a type of multi-period inventory problem with deteriorating items, in which demands are assumed to be uncertain variables. The objective is to minimize the expected total cost including the ordering cost, inventory holding cost and deteriorating cost under constraints that demands should be satisfied with some service level in each period. To solve the model, two methods are proposed in different cases. When uncertain variables are linear, a crisp equivalent form of the model is provided. For the general cases, a hybrid algorithm integrating the 99-method and genetic algorithm is designed. Two examples are given to illustrate the effectiveness of the model and solving methods.

In this paper, we develop an inventory-based approach to analyze the option market making activity. Indeed, we formulate and analytically solve the price-setting problem of a monopolistic option market maker facing exogenous public supply and demand first on a single exercise price (the "single option economy") and next on multiple exercise prices (the "multi-options economy"). While in the "single option economy" the familiar result that market maker inventory and price level are inversely related holds, the same is not necessarily true in the "multi-options economy". Additionally, we examine under which theoretical condition hedging is totally effective (i.e., the variance of the market maker hedged position is zero). Last but not least, our model is fully consistent with actual option market making practices, which consist in trading hedge portfolios to reduce risk. As such, our approach can be considered as a bridge between market microstructure and standard option pricing literature.