Paper Info
Title
Corso (Collaborative Reactive Search Optimization): Blending Combinatorial And Continuous Local Search
Abstract
We propose a heuristic global optimization technique which combines combinatorial and continuous local search. The combinatorial component, based on Reactive Search Optimization, generates a trajectory of binary strings describing search districts. Each district is evaluated by random sampling and by selective runs of continuous local search. A reactive prohibition mechanisms guarantees that the search is not stuck at locally optimal districts.The continuous stochastic local search is based on the Inertial Shaker method: candidate points are generated in an adaptive search box and a moving average of the steps filters out evaluation noise and high-frequency oscillations.The overall subdivision of the input space in a tree of non-overlapping search districts is adaptive, with a finer subdivision in the more interesting input zones, potentially leading to lower local minima.Finally, a portfolio of independent CoRSO search streams (P-CoRSO) is proposed to increase the robustness of the algorithm.An extensive experimental comparison with Genetic Algorithms and Particle Swarm demonstrates that CoRSO and P-CoRSO reach results which are fully competitive and in some cases significantly more robust.
Year
DOI
Venue
2016
10.15388/Informatica.2016.86
INFORMATICA
Keywords
Field
DocType
global optimization, reactive search optimization, algorithm portfolios
Mathematical optimization,Computer science,Local search (optimization),Reactive search optimization
Journal
Volume
Issue
ISSN
27
2
0868-4952
Citations 
PageRank 
References 
0
0.34
5
Authors
2
Name
Order
Citations
PageRank
Mauro Brunato140533.73
Roberto Battiti21937262.40