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In this paper, we study a stochastic recursive optimal control problem in which the cost functional is described by the solution of a backward stochastic differential equation driven by G-Brownian motion. Under standard assumptions, we…

Optimization and Control · Mathematics 2014-10-15 Mingshang Hu , Shaolin Ji

In planning problems, it is often challenging to fully model the desired specifications. In particular, in human-robot interaction, such difficulty may arise due to human's preferences that are either private or complex to model.…

Robotics · Computer Science 2021-01-01 Mahsa Ghasemi , Evan Scope Crafts , Bo Zhao , Ufuk Topcu

We consider a discounted reward control problem in continuous time stochastic environment where the discount rate might be an unbounded function of the control process. We provide a set of general assumptions to ensure that there exists a…

Probability · Mathematics 2016-02-17 Dariusz Zawisza

We consider a stochastic optimal control problem governed by a stochastic differential equation with delay in the control. Using a result of existence and uniqueness of a sufficiently regular mild solution of the associated…

Probability · Mathematics 2021-03-22 F. Gozzi , F. Masiero

We develop a novel mathematical programming approximation framework to tackle the stochastic knapsack problem. In this problem, the decision maker considers items for which either weights or values, or both, are random. The aim is to select…

Optimization and Control · Mathematics 2025-12-18 Roberto Rossi , Steven D. Prestwich , S. Armagan Tarim

Resource allocation is an essential aspect of successful Product Development (PD). In this paper, we formulate the dynamic resource allocation of the PD process as a convex optimization problem. Specially, we build and solve two variants of…

Systems and Control · Electrical Eng. & Systems 2020-09-22 Chengyan Zhao , Masaki Ogura , Masako Kishida , Ali Yassine

Optimization of decision problems in stochastic environments is usually concerned with maximizing the probability of achieving the goal and minimizing the expected episode length. For interacting agents in time-critical applications,…

Artificial Intelligence · Computer Science 2007-05-23 Balint Takacs , Istvan Szita , Andras Lorincz

Product ranking is the core problem for revenue-maximizing online retailers. To design proper product ranking algorithms, various consumer choice models are proposed to characterize the consumers' behaviors when they are provided with a…

Machine Learning · Computer Science 2023-01-03 Renzhe Xu , Xingxuan Zhang , Bo Li , Yafeng Zhang , Xiaolong Chen , Peng Cui

We study a stochastic control approach to managed futures portfolios. Building on the Schwartz 97 stochastic convenience yield model for commodity prices, we formulate a utility maximization problem for dynamically trading a single-maturity…

Mathematical Finance · Quantitative Finance 2018-11-06 Tim Leung , Raphael Yan

This paper introduces the formalism required to analyze a certain class of stochastic control problems that involve a super diffusion as the underlying controlled system. To establish the existence of these processes, we show that they are…

Probability · Mathematics 2024-11-19 Antonio Ocello

We consider a stochastic control problem with the assumption that the system is controlled until the state process breaks the fixed barrier. Assuming some general conditions, it is proved that the resulting Hamilton Jacobi Bellman equations…

Optimization and Control · Mathematics 2025-03-24 Dariusz Zawisza

This study introduces a mathematical framework to investigate the viability and reachability of production systems under constraints. We develop a model that incorporates key decision variables, such as pricing policy, quality investment,…

Optimization and Control · Mathematics 2025-09-16 Achraf Bouhmady , Mustapha Serhani , Nadia Raissi

We consider a Bayesian adaptive optimal stochastic control problem where a hidden static signal has a non-separable influence on the drift of a noisy observation. Being allowed to control the specific form of this dependence, we aim at…

Optimization and Control · Mathematics 2025-12-22 Alexander M. G. Cox , Sigrid Källblad , Chaorui Wang

In multi-period stochastic optimization problems, the future optimal decision is a random variable whose distribution depends on the parameters of the optimization problem. We analyze how the expected value of this random variable changes…

Optimization and Control · Mathematics 2020-01-28 Bar Light

This paper addresses a novel data science problem, prescriptive price optimization, which derives the optimal price strategy to maximize future profit/revenue on the basis of massive predictive formulas produced by machine learning. The…

Optimization and Control · Mathematics 2016-05-25 Shinji Ito , Ryohei Fujimaki

In this paper, a stochastic optimal control problem is investigated in which the system is governed by a stochastic functional differential equation. In the framework of functional It\^o calculus, we build the dynamic programming principle…

Optimization and Control · Mathematics 2013-01-03 Shaolin Ji , Shuzhen Yang

Proceeding from the concept of rational expectations, a new dynamic model of supply and demand in a single market with one supplier, one buyer, and one kind of commodity is developed. Unlike the cob-web dynamic theories with adaptive…

General Physics · Physics 2007-05-23 V. Granik , A. Granik

We consider the problem of supply and demand balancing that is stated as a minimization problem for the total expected revenue function describing the behavior of both consumers and suppliers. In the considered market model we assume that…

Optimization and Control · Mathematics 2021-06-29 Dmitry Pasechnyuk , Pavel Dvurechensky , Sergey Omelchenko , Alexander Gasnikov

In this paper, we explore a new class of stochastic control problems characterized by specific control constraints. Specifically, the admissible controls are subject to the ratcheting constraint, meaning they must be non-decreasing over…

Optimization and Control · Mathematics 2024-12-17 Mingxin Guo , Zuo Quan Xu

We provide an overview on how to use the measurable selection techniques to derive the dynamic programming principle for a general stochastic optimal control/stopping problem. By considering its martingale problem formulation on the…

Optimization and Control · Mathematics 2024-10-03 Nicole El Karoui , Xiaolu Tan