Electronic Market Place for Returned Products in The Publishing Industry: A Simulation Analysis

In the publishing industry, the publishers supply products like the magazines, newspapers and books to the retailers. In order to encourage the retailers to order more, the publishers usually adopt a kind of buy-back return policies under which the retailers can return the unsold products for a partial refund. In the past, due to the lack of retail sales channel, most of the returned products were salvaged at a very low value. Now, with the advance of e-commerce, publishers can make use of Internet as an e-marketplace to sell those returned products to a completely different market – the World Wide Web. Since Internet offers a global open system, it breaks the geographical barrier and the demand for those “locally fade-out” goods can be very significant. In light of this, we study in this paper a two-echelon supply chain with one publisher and multiple retailers. Through the simulation analysis, we find that the impact of the e-marketplace can be substantial. Depending on the operations cost of the emarketplace and the size of the demand, the expected profit improvements for the publisher, the retailers and the overall supply chain vary. We identify the factors that can achieve the situation under which all parties\u27 profits are improved with the e-marketplace. Moreover, with a price dependent demand distribution for the e-marketplace, we can determine the optimal buy-back price and the optimal emarketplace selling price for the product. A real case of a local publisher has been chosen for simulation analysis and the managerial issues are discussed

Single-Period Two-Product Inventory Model with Substitution

In this paper we study a single-period two -product inventory model with stochastic demands, proportional revenues and costs, substitution. We focus on full downward substitution in our study. We assume that the orders have to be placed before the demands are realized. And the problem is to decide the ordering quantity for each product. We develop a general profit maximization model for single-period two -product substitution problem, and show that it is concave and submodular. And we develop the optimization condition for the problem and rewrite the solution of the problem in a perfect form, which is similar to the solution of the newsboy problem. Then we compare the solution of this problem with the solution of newsboy problem, and proof that the profit can be improved using the substitution policy. For the optimization solution, we study the effects of the parameters, such as the purchase cost, the penalty cost, the salvage value, the sale price. And we can get some interesting properties of the solution with respect to the parameters, and so we can know some instructions to adjust the order quantities while the parameters are changed. From the properties, we can find out the parameters that have stronger effects on the order quantities, and pay more attention on them while making the ordering decision

Optimal inventory decisions in a multiperiod newsvendor problem with partially observed Markovian supply capacities

This paper considers a multi-period news-vendor problem with partially observed supply-capacity information which evolves as a Markovian Process. The supply capacity is fully observed by the buyer when the capacity is smaller than the buyer's ordering quantity. Otherwise, the buyer knows that the current-period supply capacity is greater than its ordering quantity. Based on these two observations, the buyer updates the future supply-capacity forecasting accordingly. With a dynamic programming formulation, we prove the existence of an optimal ordering policy. We also prove that the optimal order quantity is greater than the myopic order quantity.Partial information Markovian process Inventory planning and control Capacity learning

Approximating an Optimal Production Policy in a Continuous Flow Line: Recurrence and Asymptotic Properties

This work is concerned with manufacturing systems with two failure-prone tandem machines. The production is regulated by a continuous version of buffer control. Our goal is to obtain an optimal buffer-control policy to minimize a long run average cost function. Concentrating on threshold type of control policies, our effort is devoted to parameter optimization problems for the continuous material produce-to-stock models. We estimate the gradients of the cost function with respect to the parameter using perturbation analysis techniques, and approximate the optimal value of the parameter via a constant step-size stochastic approximation algorithm. An analysis for error accumulation in perturbation propagation is undertaken, and a sufficient condition for breaking the propagation chain is derived. In addition, we show that the event of breaking the perturbation propagation chain is recurrent if the system has sufficient capacity, derive the consistency of the gradient estimators, and esta..