Search Results - stochastic integer programming

A study of progressive hedging for stochastic integer programming

Authors: Jeffrey Christiansen Brian Dandurand Andrew Eberhard et al.

Contributors: Jeffrey Christiansen Brian Dandurand Andrew Eberhard et al.

Source: Computational Optimization and Applications. 86:989-1034

Subject Terms: 0211 other engineering and technologies, Gauss–Seidel methods, 02 engineering and technology, 0101 mathematics, Variational analysis, 01 natural sciences, Progressive hedging, Stochastic mixed integer programming

File Description: application/pdf

Access URL: https://aaltodoc.aalto.fi/handle/123456789/124842

Reputation-Aware Federated Learning Client Selection Based on Stochastic Integer Programming

Authors: Xavier Tan Wei Chong Ng Wei Yang Bryan Lim et al.

Source: IEEE Transactions on Big Data. 10:953-964

A stochastic dual dynamic integer programming based approach for remanufacturing planning under uncertainty.

Authors: Quezada, Franco Gicquel, Céline Kedad-Sidhoum, Safia

Source: International Journal of Production Research. Sep2023, Vol. 61 Issue 17, p5992-6012. 21p. 5 Charts, 2 Graphs.

Subject Terms: *INTEGER programming, *DYNAMIC programming, *REMANUFACTURING, *PRODUCTION planning, STOCHASTIC programming, UNCERTAIN systems

A Branch-and-Price Algorithm for Multistage Stochastic Integer Programming with Application to Stochastic Batch-Sizing Problems

Authors: Lulli, Guglielmo Sen, Suvrajeet

Source: Management Science, 2004 Jun 01. 50(6), 786-796.

Access URL: https://www.jstor.org/stable/30046118

Interval Two-Stage Stochastic Integer Programming for Urban Water Resource Management under Uncertainty

Authors: Mo, Shuhong Duan, Haini Shen, Bing et al.

Source: Journal of Coastal Research, 2015 Dec 01, 160-165.

Access URL: https://www.jstor.org/stable/43843258

Stochastic Integer Programming: Limit Theorems and Confidence Intervals

Authors: Eichhorn, Andreas Römisch, Werner

Source: Mathematics of Operations Research, 2007 Feb 01. 32(1), 118-135.

Access URL: https://www.jstor.org/stable/25151776

A stochastic integer programming approach to reserve staff scheduling with preferences.

Authors: Perreault‐Lafleur, Carl Carvalho, Margarida Desaulniers, Guy

Source: International Transactions in Operational Research. Jan2025, Vol. 32 Issue 1, p289-313. 25p.

Subject Terms: *JOB satisfaction, *INTEGER programming, *SCHEDULING, STOCHASTIC programming, INTEGERS

A study of progressive hedging for stochastic integer programming

Authors: Christiansen, Jeffrey Dandurand, Brian Eberhard, Andrew et al.

Source: COMPUTATIONAL OPTIMIZATION AND APPLICATIONS.

Subject Terms: ta113, ta111, Gauss–Seidel methods, Variational analysis, Progressive hedging, Stochastic mixed integer programming

Access URL: http://juuli.fi/Record/0677024423

Solving stochastic integer-programming problems in electric bus introduction planning

Authors: Y. Ishitani T. Sato T. Shiina et al.

Source: 2022 12th International Congress on Advanced Applied Informatics (IIAI-AAI). :615-620

Subject Terms: 0211 other engineering and technologies, 02 engineering and technology

Optimizing Technician Staffing and Scheduling in Medical Procedure Services Using Two-Stage Stochastic Integer Programming

Authors: Mirui Zhang Narges Shahraki Feifan Wang

Source: IEEE Transactions on Automation Science and Engineering. :1-1

Joint Optimization of Airport Slot Allocation and Gate Assignment: A Stochastic Integer Programming Approach

Authors: Xuanji Long Mingzhi Lyu Wei Liu

Algorithms for Distributionally Risk-Receptive and Robust Stochastic Integer Programs and Interdiction Problems

Authors: Kang, Sumin Industrial and Systems Engineering Bansal, Manish et al.

Contributors: Kang, Sumin Industrial and Systems Engineering Bansal, Manish et al.

Subject Terms: Decomposition Method, Stochastic Integer Programming, Interdiction Problem, Distributionally Risk-Receptive Optimization, Distributionally Robust Optimization

File Description: ETD; application/pdf

Access URL: https://hdl.handle.net/10919/137507

Continuity Properties of Expectation Functions in Stochastic Integer Programming

Authors: Schultz, Rüdiger

Source: Mathematics of Operations Research, 1993 Aug 01. 18(3), 578-589.

Access URL: https://www.jstor.org/stable/3690091

Stochastic Dual Dynamic integer Programming for a multi-echelon lot-sizing problem with remanufacturing and lost sales

Authors: Quezada, Franco Gicquel, Céline Kedad-Sidhoum, Safia

Contributors: Quezada, Franco Gicquel, Céline Kedad-Sidhoum, Safia

Source: 2019 6th International Conference on Control, Decision and Information Technologies (CoDIT). :1254-1259

Subject Terms: 0211 other engineering and technologies, 02 engineering and technology, [INFO.INFO-RO] Computer Science [cs]/Operations Research [math.OC]

Access URL: https://dblp.uni-trier.de/db/conf/codit/codit2019.html#QuezadaGK19
https://hal.archives-ouvertes.fr/hal-02421713
https://ieeexplore.ieee.org/document/8820709
https://hal.science/hal-02421713v1
https://doi.org/10.1109/codit.2019.8820709

A Stochastic Integer Programming Approach to Air Traffic Scheduling and Operations

Authors: Kai Wang Alexandre Jacquillat

Source: Operations Research. 68:1375-1402

Subject Terms: 8. Economic growth, 0211 other engineering and technologies, 02 engineering and technology

Access URL: http://doi.org/10.1287/opre.2020.1985
https://dblp.uni-trier.de/db/journals/ior/ior68.html#WangJ20
https://dialnet.unirioja.es/servlet/articulo?codigo=7597317
https://doi.org/10.1287/opre.2020.1985
https://dl.acm.org/doi/10.1287/opre.2020.1985
https://pubsonline.informs.org/doi/10.1287/opre.2020.1985

Efficient sequential and parallel algorithms for multistage stochastic integer programming using proximity

Authors: Cslovjecsek, Jana Eisenbrand, Friedrich Pilipczuk, Michał et al.

Contributors: Cslovjecsek, Jana Eisenbrand, Friedrich Pilipczuk, Michał et al.

Source: Leibniz International Proceedings in Informatics (LIPIcs), 204
29th Annual European Symposium on Algorithms (ESA 2021)
Leibniz International Proceedings in Informatics, 204

Subject Terms: FOS: Computer and information sciences, parameterized algorithm, Multistage stochastic programming, Proximity, 0211 other engineering and technologies, proximity, 0102 computer and information sciences, 02 engineering and technology, Computational Complexity (cs.CC), 01 natural sciences, Computer Science - Computational Complexity, Optimization and Control (math.OC), Parameterized algorithm, Computer Science - Data Structures and Algorithms, FOS: Mathematics, Data Structures and Algorithms (cs.DS), ddc:004, Mathematics - Optimization and Control, multistage stochastic programming

File Description: application/pdf; application/application/pdf

Access URL: http://arxiv.org/abs/2012.11742
https://dblp.uni-trier.de/db/journals/corr/corr2012.html#abs-2012-11742
https://arxiv.org/pdf/2012.11742
https://doi.org/10.4230/LIPIcs.ESA.2021.33
https://drops.dagstuhl.de/opus/volltexte/2021/14614/
https://drops.dagstuhl.de/opus/volltexte/2021/14614/pdf/LIPIcs-ESA-2021-33.pdf/
https://www.research-collection.ethz.ch/handle/20.500.11850/507027
https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2021.33
http://hdl.handle.net/20.500.11850/507027

An approximate dynamic programming approach for multi-stage stochastic lot-sizing under a Decision–Hazard–Decision information structure.

Authors: Spitzer, Victor Gicquel, Céline Gurevsky, Evgeny et al.

Source: Discrete Applied Mathematics. Jan2026, Vol. 379, p355-378. 24p.

A new risk-based optimisation method for the iron ore production scheduling using stochastic integer programming

Authors: Erkan Topal Bruce Sommerville Oktay Erten et al.

Source: Resources Policy. 62:571-579

Subject Terms: 0211 other engineering and technologies, 02 engineering and technology

File Description: restricted

Access URL: https://espace.curtin.edu.au/handle/20.500.11937/71984
https://research.nu.edu.kz/en/publications/a-new-risk-based-optimisation-method-for-the-iron-ore-production--2
https://ideas.repec.org/a/eee/jrpoli/v62y2019icp571-579.html
https://www.sciencedirect.com/science/article/pii/S0301420717302763

On the Value of Risk-Averse Multistage Stochastic Programming in Capacity Planning.

Authors: Yu, Xian Shen, Siqian

Source: INFORMS Journal on Computing. Sep/Oct2025, Vol. 37 Issue 5, p1143-1162. 20p.

Subject Terms: *RISK aversion, *STOCHASTIC programming, *OPERATING costs, *DECISION making, *DECISION trees, *CAPACITY requirements planning, *APPROXIMATION algorithms, *ECONOMIC demand

Enhancing a Branch-and-Bound Algorithm for Two-Stage Stochastic Integer Network Design-Based Models

Authors: Andrade, Rafael Lisser, Abdel Maculan, Nelson et al.

Source: Management Science, 2006 Sep 01. 52(9), 1450-1455.

Access URL: https://www.jstor.org/stable/20110616