On the Design of Metaheuristics-Based Algorithm Portfolios

2018 ◽  
pp. 271-284
Author(s):  
Dimitris Souravlias ◽  
Konstantinos E. Parsopoulos
Keyword(s):  
Algorithm Portfolios

scholarly journals SATzilla: Portfolio-based Algorithm Selection for SAT

2008 ◽  
Vol 32 ◽  
pp. 565-606 ◽  
Author(s):  
L. Xu ◽  
F. Hutter ◽  
H. H. Hoos ◽  
K. Leyton-Brown
Keyword(s):  
Traditional Approach ◽  
Data Sets ◽  
Algorithm Selection ◽  
New Techniques ◽  
Algorithm Portfolios ◽  
Predicting Performance ◽  
Different Types ◽  
Sat Solver ◽  
Selection For ◽  
Problem Instances

It has been widely observed that there is no single "dominant" SAT solver; instead, different solvers perform best on different instances. Rather than following the traditional approach of choosing the best solver for a given class of instances, we advocate making this decision online on a per-instance basis. Building on previous work, we describe SATzilla, an automated approach for constructing per-instance algorithm portfolios for SAT that use so-called empirical hardness models to choose among their constituent solvers. This approach takes as input a distribution of problem instances and a set of component solvers, and constructs a portfolio optimizing a given objective function (such as mean runtime, percent of instances solved, or score in a competition). The excellent performance of SATzilla was independently verified in the 2007 SAT Competition, where our SATzilla07 solvers won three gold, one silver and one bronze medal. In this article, we go well beyond SATzilla07 by making the portfolio construction scalable and completely automated, and improving it by integrating local search solvers as candidate solvers, by predicting performance score instead of runtime, and by using hierarchical hardness models that take into account different types of SAT instances. We demonstrate the effectiveness of these new techniques in extensive experimental results on data sets including instances from the most recent SAT competition.

On algorithm portfolios and restart strategies

2011 ◽  
Vol 39 (1) ◽  
pp. 49-52 ◽  
Author(s):  
Oleg V. Shylo ◽  
Oleg A. Prokopyev ◽  
Jayant Rajgopal
Keyword(s):  
Algorithm Portfolios

On Maximum Speedup Ratio of Restart Algorithm Portfolios

2013 ◽  
Vol 25 (2) ◽  
pp. 222-229 ◽  
Author(s):  
Oleksii Mostovyi ◽  
Oleg A. Prokopyev ◽  
Oleg V. Shylo
Keyword(s):  
Algorithm Portfolios ◽  
Speedup Ratio

NeuroEAs-based algorithm portfolios for classification problems

2012 ◽  
Author(s):  
Supawadee Srikamdee ◽  
Sunisa Rimcharoen ◽  
Krisana Chinnasarn
Keyword(s):  
Classification Problems ◽  
Algorithm Portfolios

scholarly journals Population-Based Algorithm Portfolios for Numerical Optimization

2010 ◽  
Vol 14 (5) ◽  
pp. 782-800 ◽  
Author(s):  
Fei Peng ◽  
Ke Tang ◽  
Guoliang Chen ◽  
Xin Yao
Keyword(s):  
Numerical Optimization ◽  
Population Based ◽  
Algorithm Portfolios ◽  
Population Based Algorithm

Algorithm Portfolios

2021 ◽  
pp. 13-21
Author(s):  
Dimitris Souravlias ◽  
Konstantinos E. Parsopoulos ◽  
Ilias S. Kotsireas ◽  
Panos M. Pardalos
Keyword(s):  
Algorithm Portfolios
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