Joint Pricing and Inventory Control with a Markovian Demand Model PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Joint Pricing and Inventory Control with a Markovian Demand Model PDF full book. Access full book title Joint Pricing and Inventory Control with a Markovian Demand Model by Rui Yin. Download full books in PDF and EPUB format.
Author: Rui Yin Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
We consider the joint pricing and inventory control problem for a single product with a finite horizon and periodic review. The demand distribution in each period is determined by an exogenous Markov chain. Pricing and ordering decisions are made at the beginning of each period and all shortages are backlogged. The surplus costs as well as fixed and variable costs are state dependent. We show the existence of an optimal (s, S, p)-type feedback policy for the additive demand model. We extend the model to the case of emergency orders and also incorporate capacity and service level constraints. We compute the optimal policy for a class of Markovian demand and illustrate the benefits of dynamic pricing over fixed pricing strategies through numerical examples. The results indicate that it is more beneficial to implement the dynamic pricing strategy in a Markovian demand environment with a high fixed ordering cost or with high demand uncertainty.
Author: Rui Yin Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
We consider the joint pricing and inventory control problem for a single product with a finite horizon and periodic review. The demand distribution in each period is determined by an exogenous Markov chain. Pricing and ordering decisions are made at the beginning of each period and all shortages are backlogged. The surplus costs as well as fixed and variable costs are state dependent. We show the existence of an optimal (s, S, p)-type feedback policy for the additive demand model. We extend the model to the case of emergency orders and also incorporate capacity and service level constraints. We compute the optimal policy for a class of Markovian demand and illustrate the benefits of dynamic pricing over fixed pricing strategies through numerical examples. The results indicate that it is more beneficial to implement the dynamic pricing strategy in a Markovian demand environment with a high fixed ordering cost or with high demand uncertainty.
Author: Lisa Gimpl-Heersink Publisher: Peter Lang Pub Incorporated ISBN: 9783631589137 Category : Business & Economics Languages : en Pages : 124
Book Description
In this work, we address the problem of simultaneously determining a pricing and inventory replenishment strategy under reference price effects. This reference price effect models the fact that consumers not only react sensitively to the current price, but also to deviations from a reference price formed on the basis of past purchases. Immediate effects of price reductions on profits have to be weighted against the resulting losses in future periods. By providing an analytical analysis and numerical simulations we study how the additional dynamics of the consumers' willingness to pay affect an optimal pricing and inventory control model and whether a simple policy such as a base-stock-list-price policy holds in such a setting.
Author: Emel Arikan Publisher: ISBN: Category : Languages : en Pages : 116
Book Description
The price-setting newsvendor model is used to address the single period joint pricing and inventory control problem. The objective is to set the optimal price and replenishment quantity of a single product in order to maximize the expected profit. Products with a short selling season and relatively long replenishment lead times such as fashion goods are the most relevant application areas of the model. The focus of the work is the generalization of the model with respect to the modeling of uncertainty in demand. The author presents an analytical and empirical study which compares different demand models with a more flexible model based on price and inventory optimization. She concludes that using a general model can increase the profits significantly.
Author: Yifeng Liu Publisher: ISBN: Category : Inventory control Languages : en Pages : 127
Book Description
Effective pricing and inventory controls are very important for the success of a company, especially in an environment with many uncertainties such as random demand and fluctuating cost. In this work, we first consider pure dynamic pricing. Indeed, we consider three cases: markup in which price can only go up, markdown in which price can only go down, and reversible pricing in which price can go either direction. We also consider a joint pricing and inventory control model in which the raw material price evolves as a Markov process. For this model, we suppose production is make-to-order, so that the conversion from raw material to finished product is carried out only when demand arrives. For the pure pricing model, we establish the optimality of threshold-like policies. We also develop efficient and numerically stable algorithms. For the make-to-order joint inventory-pricing model, we demonstrate the optimality of a base-stock-list-price policy. In addition, we identify conditions under which policy parameters would exhibit monotone trends. Moreover, we showed the significant benefit of adopting cost-dependent base-stock list-price policy.
Author: Hanzhang Qin (S. M.) Publisher: ISBN: Category : Languages : en Pages : 96
Book Description
The thesis studies the classical multi-period joint pricing and inventory control problem in a data-driven setting. In the problem, a retailer makes periodic decisions of the prices and inventory levels of an item that the retailer wishes to sell. The objective is to match the inventory level with a random demand that depends on the price in each period, while maximizing the expected profit over finite horizon. In reality, the demand functions or the distribution of the random noise are usually unavailable, whereas past demand data are relatively easy to collect. A novel data-driven nonparametric algorithm is proposed, which uses the past demand data to solve the joint pricing and inventory control problem, without assuming the parameters of the demand functions and the noise distributions are known. Explicit sample complexity bounds are given, on the number of data samples needed to guarantee a near-optimal profit. A simulation study suggests that the algorithm is efficient in practice.
Author: Anupam Mazumdar (S. M.) Publisher: ISBN: Category : Languages : en Pages : 81
Book Description
Price management, production planning and inventory control are important determinants of a firm's profitability. The intense competition brought about by rapid innovation, lean manufacturing time and the internet revolution has compelled firms to adopt a dynamic strategy that involves complex interplay between pricing and production decisions. In this thesis we consider some of these problems and develop computationally efficient algorithms that aim to tackle and optimally solve these problems in a finite amount of time. In the first half of the thesis we consider the joint pricing and inventory control problem in a deterministic and multiperiod setting utilizing the popular log linear demand model. We develop four algorithms that aim to solve the resulting profit maximization problem in a finite amount of time. The developed algorithms are then tested in a variety of settings ranging from small to large instances of trial data. The second half of the thesis deals with setting prices effectively when the customer demand is assumed to follow the multinomial logit demand model, which is the most popular discrete choice demand model. The profit maximization problem (even in the absence of constraints) is non-convex and hard to solve. Despite this fact we develop algorithms that compute the optimal solution efficiently. We test the algorithms we develop in a wide variety of scenarios from small to large customer segment, with and without production/inventory constraints. The last part of the thesis develops solution methods for the joint pricing and inventory control problem when costs are linear and demand follows the multinomial logit model.
Author: Özalp Özer Publisher: Oxford University Press (UK) ISBN: 0199543178 Category : Business & Economics Languages : en Pages : 977
Book Description
A definitive reference to the theory and practice of pricing across industries, environments, and methodologies. It covers all major areas of pricing including, pricing fundamentals, pricing tactics, and pricing management.
Author: Dirk Beyer Publisher: Springer Science & Business Media ISBN: 0387716041 Category : Business & Economics Languages : en Pages : 260
Book Description
This text provides a superbly researched insight into Markovian demand inventory models. The result of ten years of research, this work covers all aspects of demand inventory where they are modeled by Markov processes. Inventory management is concerned with matching supply with demand and is a central problem in Operations Management. The central problem is to find the amount to be produced or purchased in order to maximize the total expected profit, or minimize the total expected cost.
Author: Rui Yin
Author: Rui Yin
Author: Lisa Gimpl-Heersink
Author: Emel Arikan
Author: Yifeng Liu
Author: Hanzhang Qin
Author: Hanzhang Qin (S. M.)
Author: Anupam Mazumdar (S. M.)
Author: Karin Möllering
Author: Özalp Özer
Author: Dirk Beyer