Non-cooperative competition among revenue maximizing service providers with demand learning |
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Authors: | Changhyun Kwon Terry L Friesz Reetabrata Mookherjee Tao Yao Baichun Feng |
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Institution: | 1. Department of Industrial and Manufacturing Engineering, The Pennsylvania State University, University Park, PA 16802, USA;2. Zilliant Inc., 3815 S Capital of Texas Hwy, Suite 300, Austin, TX 78704, USA |
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Abstract: | This paper recognizes that in many decision environments in which revenue optimization is attempted, an actual demand curve and its parameters are generally unobservable. Herein, we describe the dynamics of demand as a continuous time differential equation based on an evolutionary game theory perspective. We then observe realized sales data to obtain estimates of parameters that govern the evolution of demand; these are refined on a discrete time scale. The resulting model takes the form of a differential variational inequality. We present an algorithm based on a gap function for the differential variational inequality and report its numerical performance for an example revenue optimization problem. |
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Keywords: | Revenue management Pricing Demand learning Differential games Kalman filters |
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