Mehdi Hemmati – Optimization Online

Approximate solution of infinite-horizon risk-sensitive Markov decision processes

Published: 2026/07/15, Updated: 2026/08/21

Dynamic Programming, Other Topics Markov Decision Process, risk sensitivity, sequential decision making

Infinite-horizon risk-sensitive Markov decision processes (MDPs) under the discounted cost criterion are challenging to solve because the optimal policy may be nonstationary. Existing methods typically reformulate the problem as a continuous-state risk-neutral MDP and rely on state discretization or value-function approximation, often without explicit stopping conditions or error bounds. In this paper, we present approximate … Read more

Relating Single-Scenario Facets to the Convex Hull of the Extensive Form of a Stochastic Single-Node Flow Polytope

Published: 2019/06/25, Updated: 2020/03/27

(Mixed) Integer Linear Programming, Polyhedra, Stochastic Programming facets, polyhedral combinatorics, stochastic mixed-integer programming

Stochastic mixed-integer programs (SMIPs) are a widely-used modeling paradigm for sequential decision making under uncertainty. One popular solution approach to solving SMIPs is to solve the so-called “extensive form” directly as a large-scale (deterministic) mixed-integer program. In this work, we consider the question of when a facet-defining inequality for the convex hull of a deterministic, … Read more