Markov yapıda değişen talebe bağlı hasılat yönetimi

The admission decision is one of the fundamental categories of demand-management decisions. In the dynamic model of the single-resource capacity control problem, distribution of demand at each stage is known, but it is either fixed or time-dependent. However, in reality demand may depend on the current external environment which represents the prevailing economic, financial, social or other factors that affect customer behavior. In this thesis, we formulate a Markov decision process (MDP) model in which the state of the process is described by the remaining inventory level and the current environment. We derive some structural results for this MDP model, including the existence of an environment-dependent threshold policy and a comparison of threshold levels in different environments. Then we extend our study to a dynamic pricing problem in which there is only one type of product and the objective is to find the optimal pricing policy to maximize the revenue of the firm. Another important research topic of revenue management is modeling consumer behavior. In such models, the change in consumer behavior towards the set of products offered is also considered. We formulate a discrete choice model of consumer behavior in fluctuating demand environment with a Markovian structure. We derive some structural results on the optimal policy for revenue management. Even though there may be an environment process, we may not observe it directly. We also model such a problem in which we just observe an external process that gives a probability distribution for the true state of the current environment. This model can be classified as Hidden Markov Decision Process and we derive structural results for it. We also present some computational results for all these three models in order to illustrate our structural properties.