On the Bellman's principle of optimality

DOI10.1016/j.physa.2016.06.083zbMath1400.90295OpenAlexW2422768215MaRDI QIDQ1619876

Eitan Z. Gross

Publication date: 13 November 2018

Published in: Physica A (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.physa.2016.06.083

zbMATH Keywords

dynamic programmingMarkov decision processesprinciple of optimality

Mathematics Subject Classification ID

Dynamic programming in optimal control and differential games (49L20) Dynamic programming (90C39) Optimal stochastic control (93E20) Markov and semi-Markov decision processes (90C40)

Uses Software

• VRP

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• State aggregation in dynamic programming - an application to scheduling of independent jobs on parallel processors
• Single machine scheduling to minimize weighted earliness subject to no tardy jobs
• New results on the relationship between dynamic programming and the maximum principle
• Traditional proof of Bellman's equation for controlled diffusion processes
• Routing through a network with maximum reliability
• Dynamic Programming State-Space Relaxation for Single-Machine Scheduling
• A Method for Single Facility Multiple Products Scheduling
• Exact algorithms for the vehicle routing problem, based on spanning tree and shortest path relaxations
• Infinite Horizon Investment—Consumption Policies
• Optimal Control and Nonlinear Filtering for Nondegenerate Diffusion Processes
• An Introductory Approach to Duality in Optimal Stochastic Control
• Shortest-Route Methods: 2. Group Knapsacks, Expanded Networks, and Branch-and-Bound
• Optimal Sequential Investment Decisions Under Conditions of Uncertainty
• Open-loop routing of N arrivals to M parallel queues
• The partial differential equation u_t + uu_x = μ_xx
• On the Theory of Dynamic Programming