Sushil Varma - Academia.edu (original) (raw)
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Papers by Sushil Varma
ACM SIGMETRICS Performance Evaluation Review
Motivated by diverse applications in sharing economy and online marketplaces, we consider optimal... more Motivated by diverse applications in sharing economy and online marketplaces, we consider optimal pricing and matching control in a two-sided queueing system. We assume that heterogeneous customers and servers arrive to the system with price-dependent arrival rates. The compatibility between servers and customers is specified by a bipartite graph. Once a pair of customer and server are matched, they depart from the system instantaneously. The objective is to maximize the long-run average profits of the system while minimizing average waiting time. We first propose a static pricing and max-weight matching policy, which achieves O(√ n) optimality rate when all of the arrival rates are scaled by n. We further show that a dynamic pricing and modified max-weight matching policy achieves an improved O(n1/3) optimality rate. In addition, we propose a constraint generation algorithm that solves value function approximation of the MDP and demonstrate strong numerical performance of this algo...
ACM SIGMETRICS Performance Evaluation Review
Motivated by diverse applications in sharing economy and online marketplaces, we consider optimal... more Motivated by diverse applications in sharing economy and online marketplaces, we consider optimal pricing and matching control in a two-sided queueing system. We assume that heterogeneous customers and servers arrive to the system with price-dependent arrival rates. The compatibility between servers and customers is specified by a bipartite graph. Once a pair of customer and server are matched, they depart from the system instantaneously. The objective is to maximize the long-run average profits of the system while minimizing average waiting time. We first propose a static pricing and max-weight matching policy, which achieves O(√ n) optimality rate when all of the arrival rates are scaled by n. We further show that a dynamic pricing and modified max-weight matching policy achieves an improved O(n1/3) optimality rate. In addition, we propose a constraint generation algorithm that solves value function approximation of the MDP and demonstrate strong numerical performance of this algo...