Search results for "Greatest common divisor"
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A Learning-Automata Based Solution for Non-equal Partitioning: Partitions with Common GCD Sizes
2021
The Object Migration Automata (OMA) has been used as a powerful tool to resolve real-life partitioning problems in random Environments. The virgin OMA has also been enhanced by incorporating the latest strategies in Learning Automata (LA), namely the Pursuit and Transitivity phenomena. However, the single major handicap that it possesses is the fact that the number of objects in each partition must be equal. Obviously, one does not always encounter problems with equally-sized groups (When the true underlying problem has non-equally-sized groups, the OMA reports the best equally-sized solution as the recommended partition.). This paper is the pioneering attempt to relax this constraint. It p…
Object Migration Automata for Non-equal Partitioning Problems with Known Partition Sizes
2021
Part 4: Automated Machine Learning; International audience; Solving partitioning problems in random environments is a classic and challenging task, and has numerous applications. The existing Object Migration Automaton (OMA) and its proposed enhancements, which include the Pursuit and Transitivity phenomena, can solve problems with equi-sized partitions. Currently, these solutions also include one where the partition sizes possess a Greatest Common Divisor (GCD). In this paper, we propose an OMA-based solution that can solve problems with both equally and non-equally-sized groups, without restrictions on their sizes. More specifically, our proposed approach, referred to as the Partition Siz…