Parallel algorithm portfolios with adaptive resource allocation strategy

Algorithm portfolios are multi-algorithmic schemes that combine a number of solvers into a joint framework for solving global optimization problems. A crucial part of such schemes is the resource allocation process that is responsible for assigning computational resources to the constituent algorith...

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Bibliographic Details
Published in:Journal of global optimization Vol. 88; no. 3; pp. 685 - 705
Main Authors: Parsopoulos, Konstantinos E., Tatsis, Vasileios A., Kotsireas, Ilias S., Pardalos, Panos M.
Format: Journal Article
Language:English
Published: New York Springer US 01.03.2024
Springer
Springer Nature B.V
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ISSN:0925-5001, 1573-2916
Online Access:Get full text
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Summary:Algorithm portfolios are multi-algorithmic schemes that combine a number of solvers into a joint framework for solving global optimization problems. A crucial part of such schemes is the resource allocation process that is responsible for assigning computational resources to the constituent algorithms. We propose a resource allocation process based on adaptive decision-making procedures. The proposed approach is incorporated in algorithm portfolios composed of three essential types of numerical optimization algorithms, namely gradient-based, direct search, and swarm intelligence algorithms. The designed algorithm portfolios are experimentally demonstrated on a challenging optimization problem for different dimensions and experimental settings. The accompanying statistical analysis offers interesting conclusions and insights on the performance of the algorithm portfolio compared to its constituent algorithms, as well as on the effect of its parameters.
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ISSN:0925-5001
1573-2916
DOI:10.1007/s10898-022-01162-y