PreprintCC BY 4.0arXiv
A Robust Binary Nonlinear Solver for Multi-stage Decisions
Abstract
This document describes two developments. The first is a Multi-stage Decision Framework that permits the formulation of various sequential decision-making problems in a generic manner. The second concerns a robust stochastic solution procedure designed to handle the binary nonlinear optimization problem stemming from the proposed decision framework. The method adopts Monte-Carlo search with incremental probabilistic learning with reinforcement. The two developments are described herein along with a demonstrative application example. Key words: Multi-stage, decisions, binary, nonlinear systems, probabilistic and reinforcement learning
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BibTeX
@misc{rashid2026robust,
title = {{A Robust Binary Nonlinear Solver for Multi-stage Decisions}},
author = {Kashif Rashid},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.10145},
eprint = {2609.10145},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.10145},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - A Robust Binary Nonlinear Solver for Multi-stage Decisions
AU - Kashif Rashid
PY - 2026
DA - 2026/09/09
PB - arXiv
DO - 10.48550/arxiv.2609.10145
UR - https://arxiv.org/abs/2609.10145
AB - This document describes two developments. The first is a Multi-stage Decision Framework that permits the formulation of various sequential decision-making problems in a generic manner. The second concerns a robust stochastic solution procedure designed to handle the binary nonlinear optimization problem stemming from the proposed decision framework. The method adopts Monte-Carlo search with incremental probabilistic learning with reinforcement. The two developments are described herein along with a demonstrative application example. Key words: Multi-stage, decisions, binary, nonlinear systems, probabilistic and reinforcement learning
ER -