Studies On Capacity Allocation And Correlative Mechanisms Of Third Party Warehousing With Revenue Management

With the fast development of warehousing industry and the increasing intensity of competitive market, the revenue problem has become a hotspot that arouses great concern from the third party warehousing (3PW) companies. One of the key problems is the warehousing capacity allocation under uncertainty. Traditionally the capacity allocation aimed at lifting space utilization rate of the warehouse. But facing the current fierce competition and much lower storage rate, the third party warehousing companies cannot raise profit by lifting space utilization rate separately. Indispensable changes are required in operational practices of cost reduction or lifting space utilization rate. Instead companies are supposed to use revenue management (RM) method and allocate capacity to the cargos with higher marginal revenue contribution based on market subdivision so as to lift the profit. RM can be defined as the integration management of inventory and price to maximize a company's profitability, which has been proved effective in the airline industry for many years. Compared with the airline industry, RM practice now has not been widely used in the warehousing industry, and the relative RM studies are relatively few.Similar to airline industry, as a typical service industry, warehousing industry has the characteristics for the application of RM, such as relatively fixed and perishable capacity, advance booking, high fixed costs and lower marginal costs, stochastic but segmentable demand, fiercely competitive market and so on. Therefore RM also has considerable applicative promising in the warehousing industry. However due to the difference between airline industry and warehousing industry, the RM methods which are successfully applied in the airline passenger industry can't be copied to warehousing industry directly. Based on the analysis of the characteristics of third party warehousing RM, a third party warehousing RM concept model is developed accordingly in the thesis. A series of mathematical models are established by stochastic and dynamic programming methods for the further analysis of the container slot allocation. Robust optimization methods are introduced to solve the models to get satisfactory results in reasonable computation time. In addition, some of the parameters are evaluated and analyzed to get the right revenue management policy.Fierce competition and market changes always cause customers' demands changes which have made demand updating a special problem for 3PW RM. In order to handle this problem, continuous static newsboy models with revenue maximization are firstly established to get the optimized capacity scheme for each class of goods. With numeric simulation, best allocation policy and relative characteristic analysis of allocated capacity and service level are given. Secondly, two stochastic programming models are developed on capacity allocation, one with demand updating involved and the other without. They are transformed to linear integer programming models by the method of robust optimization. The thesis compares the results under two conditions by digital simulation, which shows the applicative value of these models and methods in solving the demand updating problem faced by 3PW companies under uncertainty.Then the thesis studies the dynamic booking control problem in warehousing capacity allocation. A dynamic and stochastic programming model is established with the similar method to solve stochastic knapsack problems. Based on the analysis of the characteristic of the model, the dynamic booking control policies are put forward based on threshold value. Finally, the optimization warehousing allocation policy is achieved by digital simulation, which shows that expecting revenue is concave function of surplus capacity, and is also concave function of booking leading time, the opportunity costs is a non-increase function of surplus capacity, and is also is a non- increase function of booking leading time. The dynamic booking control policies provide scientific foundation for real-time decision-making of 3PW companies.Finally, the thesis turns to capacity allocation problem of distribution process, which is an important part of 3PW value-added service and profit source. A stochastic programming model is developed on capacity allocation. They are transformed to linear integer programming models by the method of robust optimization. The thesis confirms the feasibility of model and method by digital simulation. Capacity allocation policy is determined by calculation, with stochastic warehousing demands and invariable process ability scheme. And then, this thesis extended the model, taking multi-degree of demands into consideration, robust optimization helped to find the optimized solution which shows the model and method effectively direct the 3PW companies in the distribution process allocation decision and consequently lift the equipment utilizations rate and the revenue level of the company.