In classical multiarmed bandit problem, the aim is to find a policy maximizing expected total reward, implicitly assuming that decision-maker risk-neutral. On other hand, decision-makers are risk-averse in some real-life applications. this article, we design new setting based on concept of dynamic risk measures where with best risk-adjusted discounted outcome. We provide theoretical analysis pr...

the paper discusses the location-allocation model for logistic networks and distribution centers through considering uncertain parameters. in real-world cases, demands and transshipment costs change over the period of the time. this may lead to large cost deviation in total cost. scenario based robust optimization approaches are proposed where occurrence probability of each scenario is not know...

In this paper, we study the problem of selecting a system that has the best performance or selecting one of the best systems when the objective function is the expected performance of a complex stochastic system. The focus here is on a huge size but finite feasible solution set, that is not necessarily well structured. We consider the use of the ordinal optimization technique that concerns with...