A Parallel Framework for Primal Heuristics in SHOT

Alireza Olama; Andreas Lundell

A Parallel Framework for Primal Heuristics in SHOT

Alireza Olama^*
, Andreas Lundell

^*Corresponding author for this work

Research output: Chapter in Book/Conference proceeding › Published conference proceeding › Scientific › peer-review

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Abstract

The Supporting Hyperplane Optimization Toolkit (SHOT) is a solver designed for Mixed-Integer Nonlinear Programming (MINLP) problems. In its current form, SHOT handles primal heuristics sequentially on a single thread, which blocks the solver’s execution until the heuristic process completes. In this work, we utilize SHOT's modular architecture to develop a new approach that enables primal heuristics to run in parallel with the main optimization process, without blocking its progress. This allows for improved efficiency and scalability of the solver. The proposed framework will be evaluated on a representative set of benchmark problems from the MINLPLib library to assess its performance and effectiveness.

Original language	English
Title of host publication	Proceedings of the Stockholm Global Optimization Workshop, STOGO 2025
Pages	137-140
Number of pages	4
Publication status	Published - 2 Sept 2025
MoE publication type	A4 Article in a conference publication
Event	Stockholm Global Optimization Workshop 2025 - Duration: 2 Sept 2025 → 5 Sept 2025 https://sites.google.com/view/stogo25/

Workshop

Workshop	Stockholm Global Optimization Workshop 2025
Abbreviated title	STOGO
Period	02/09/25 → 05/09/25
Internet address	https://sites.google.com/view/stogo25/

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Global_Optimization_2025

Algorithms and Software for Large-Scale Optimization
Lundell, A. (Principal Investigator), Björkqvist, J. (Co-Investigator), Olama, A. (Participant) & Blomqvist, J. (Participant)
01/09/23 → 30/06/26
Project: Foundation

Cite this

@inproceedings{1b74d84da9474433aabb47941fcc0cdf,

title = "A Parallel Framework for Primal Heuristics in SHOT",

abstract = "The Supporting Hyperplane Optimization Toolkit (SHOT) is a solver designed for Mixed-Integer Nonlinear Programming (MINLP) problems. In its current form, SHOT handles primal heuristics sequentially on a single thread, which blocks the solver{\textquoteright}s execution until the heuristic process completes. In this work, we utilize SHOT's modular architecture to develop a new approach that enables primal heuristics to run in parallel with the main optimization process, without blocking its progress. This allows for improved efficiency and scalability of the solver. The proposed framework will be evaluated on a representative set of benchmark problems from the MINLPLib library to assess its performance and effectiveness.",

author = "Alireza Olama and Andreas Lundell",

note = "Ej publicerad {\"a}nnu; Stockholm Global Optimization Workshop 2025, STOGO ; Conference date: 02-09-2025 Through 05-09-2025",

year = "2025",

month = sep,

day = "2",

language = "English",

pages = "137--140",

booktitle = "Proceedings of the Stockholm Global Optimization Workshop, STOGO 2025",

url = "https://sites.google.com/view/stogo25/",

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TY - GEN

T1 - A Parallel Framework for Primal Heuristics in SHOT

AU - Olama, Alireza

AU - Lundell, Andreas

N1 - Ej publicerad ännu

PY - 2025/9/2

Y1 - 2025/9/2

N2 - The Supporting Hyperplane Optimization Toolkit (SHOT) is a solver designed for Mixed-Integer Nonlinear Programming (MINLP) problems. In its current form, SHOT handles primal heuristics sequentially on a single thread, which blocks the solver’s execution until the heuristic process completes. In this work, we utilize SHOT's modular architecture to develop a new approach that enables primal heuristics to run in parallel with the main optimization process, without blocking its progress. This allows for improved efficiency and scalability of the solver. The proposed framework will be evaluated on a representative set of benchmark problems from the MINLPLib library to assess its performance and effectiveness.

AB - The Supporting Hyperplane Optimization Toolkit (SHOT) is a solver designed for Mixed-Integer Nonlinear Programming (MINLP) problems. In its current form, SHOT handles primal heuristics sequentially on a single thread, which blocks the solver’s execution until the heuristic process completes. In this work, we utilize SHOT's modular architecture to develop a new approach that enables primal heuristics to run in parallel with the main optimization process, without blocking its progress. This allows for improved efficiency and scalability of the solver. The proposed framework will be evaluated on a representative set of benchmark problems from the MINLPLib library to assess its performance and effectiveness.

M3 - Published conference proceeding

SP - 137

EP - 140

BT - Proceedings of the Stockholm Global Optimization Workshop, STOGO 2025

T2 - Stockholm Global Optimization Workshop 2025

Y2 - 2 September 2025 through 5 September 2025

ER -

A Parallel Framework for Primal Heuristics in SHOT

Abstract

Workshop

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Algorithms and Software for Large-Scale Optimization

Cite this