Inventory-based dynamic pricing has become a common operations strategy in practice and has received considerable attention from the research community. From an implementation perspective, it is desirable to design a simple policy like a base-stock list-price (BSLP) policy. The existing research on this problem often imposes restrictive conditions to ensure the optimality of a BSLP policy, which limits its applicability in practice. In this paper, we analyze the dynamic inventory and pricing control problem in which the demand follows a generalized additive model (GAM). The GAM overcomes the limitations of several demand models commonly used in the literature, but introduces analytical challenges in analyzing the dynamic program. Via a variable transformation approach, we identify a new set of technical conditions under which a BSLP policy is optimal. These conditions are easy to verify because they depend only on the location and scale parameters of demand as functions of price and are independent of the cost parameters or the distribution of the random demand component. Moreover, although a BSLP policy is optimal under these conditions, the optimal price may not be monotone decreasing in the inventory level. We further demonstrate our results by applying a constrained maximum likelihood estimation procedure to simultaneously estimate the demand function and verify the optimality of a BSLP policy on a retail data set.
In this paper, an alternate passive leg structure is proposed for the Tricept machine tool to form a modified Tricept machine tool. The global stiffness of the modified Tricept machine tool is derived and compared with that of the Tricept machine tool. First, the configurations of the Tricept machine tool and the modified Tricept machine tool are introduced, respectively. Then, the global velocity equations are derived and the stiffness models of the two configurations are presented and analyzed. Finally, the advantages and disadvantages of the two types of passive leg structure are analyzed and discussed and stiffness simulations are conducted.
This paper presents a magnetically coupling bending-torsion piezoelectric energy harvester based on vortex-induced vibration from low-speed wind. The theoretical model of the energy harvester was formulated and validated by wind tunnel experiments. Numerical and experimental results showed that the power output and bandwidth of the proposed harvester are improved about 180% and 230% respectively compared with the nonmagnetic coupling harvester. Furthermore, the effects of cylinder, piezoelectric layer, load resistance, and magnetic nonlinear parameters on the harvester were investigated based on the distributed parameter model. The results showed that the length of cylinder hardly affect output power, but the diameter of cylinder presented complicated influences. The width of piezoelectric beam was negatively correlated with the torsion angle. With increasing the length of piezoelectric layer, an optimal wind velocity and load resistance can be obtained for the maximum output power. With decreasing of the distance between two magnets, the resonant bandwidth, the optimal power output, and torsion angle can be enhanced, respectively. Besides, the magnetic potential energy increased owing to the magnetically coupling, which led to the improvement of onset speed for the energy harvester. This study provides a guideline on improving the performance of bending-torsion vibration piezoelectric energy harvester.
This paper presents the development of a pianoplaying robot in order to provide people a mean of entertainment. The design and development of this research include two parts: the design of a dexterous hand for manipulating a piano and a linear motion control system. The paper first discussed the design of dexterous hand, and a CAD model is created to examine the feasibility of the hand. Then, a motion control solution was determined, a linear railing along with a rack and pinion gear are applied to produce the linear motion. Finally, a flow chart of the control system was presented. Experimental results show the piano robot can play designated notes.
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