Approximation Algorithms for Stochastic Optimization Problems in Operations Management
نویسنده
چکیده
This article provides an introduction to approximation algorithms in stochastic optimization models arising in various application domains, including central areas of operations management, such as scheduling, facility location, vehicle routing problems, inventory and supply chain management and revenue management. Unfortunately, these models are very hard to solve to optimality both in theory and practice. We will survey recent development on approximation algorithms for these stochastic optimization models and their performance analysis techniques with worst-case performance guarantees.
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