In this paper, we consider a newsvendor problem commonly encountered in retail stores that cater to budget-sensitive shoppers. The newsvendor sells multiple products, and in addition to determining order quantities must also determine the selling price of each product sold. The demand for each...

A large class of problems of sequential decision making under uncertainty, of which the underlying probability structure is a Markov process, can be modeled as stochastic dynamic programs (referred to, in general, as Markov decision problems or MDPs). However, the computational complexity of the...

Bulk-arrival queues with single servers that provide bulk service are widespread in the real world, e.g., elevators in buildings, people-movers in amusement parks, air-cargo delivery planes, and automated guided vehicles. Much of the literature on this topic focusses on the development of the...

Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduces the evolving area of static and dynamic simulation-based optimization. Covered in detail are model-free optimization techniques - especially designed for those discrete-event, stochastic...

Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduces the evolving area of simulation-based optimization. The book's objective is two-fold: (1) It examines the mathematical governing principles of simulation-based optimization, thereby providing...