Surveys in Operations Research and Management Science 

TL;DR: In this paper, the authors survey the literature on non-convex mixed-integer nonlinear programs, discussing applications, algorithms, and software, and special attention is paid to the case in which the objective and constraint functions are quadratic.

TL;DR: An overview of the use of Monte Carlo sampling-based methods for stochastic optimization problems with sampling is given, with the goal of introducing the topic to students and researchers and providing a practical guide for someone who needs to solve a stochastically optimization problem with sampling.

TL;DR: In this paper, the authors provide a brief introduction to the historical origins of quantitative research on pricing and demand estimation, point to different subfields in the area of dynamic pricing, and provide an in-depth overview of the available literature on dynamic pricing and learning.

TL;DR: In this paper, a quadrangle of risk is developed to reconcile risk measures and expected utility, thereby reconciling those two approaches to optimisation under uncertainty, and a direct correspondence can be identified between measures of error and measures of regret.

TL;DR: The most recent advances in the context of decision making under uncertainty are surveyed, with an emphasis on the modeling of risk-averse preferences using the apparatus of axiomatically defined risk functionals and their connection to utility theory, stochastic dominance, and other more established methods.