6533b855fe1ef96bd12b0763

RESEARCH PRODUCT

Parallel Random Search and Tabu Search for the Minimal Consistent Subset Selection Problem

Ariadna FuertesVicente Cerverón

subject

Random searchMathematical optimizationSearch engineSearch algorithmComputer scienceFace (geometry)Guided Local SearchHill climbingAlgorithmSelection (genetic algorithm)Tabu search

description

The Minimal Consistent Subset Selection (MCSS) problem is a discrete optimization problem whose resolution for large scale instances requires a prohibitive processing time. Prior algorithms addressing this problem are presented. Randomization and approximation techniques are suitable to face the problem, then random search and meta-heuristics are proposed and consequently Tabu Search strategies are applied and evaluated. Parallel computing helps to reduce processing time and/or produce better results; different approaches for designing parallel tabu search are analyzed.

yearjournalcountryeditionlanguage
1998-01-01
https://doi.org/10.1007/3-540-49543-6_20