activity
20122026
most citedReplicable Parallel Branch and Bound Search

19 citations · 56 across the 10 of their papers we have counts for

collaborators

12 papers

cs.LO2026

Introducing The Maximum Common Bigraph Problem

Kyle Burns, Michele Sevegnani, Ciaran McCreesh +1

Bigraph reactive systems offer a powerful and flexible mathematical framework for modelling both spatial and non-spatial relationships between agents, with practical applications i…

cs.LO2025★ 1 cited

Faster Certified Symmetry Breaking Using Orders With Auxiliary Variables

Markus Anders, Bart Bogaerts, Benjamin Bogø +8

Symmetry breaking is a crucial technique in modern combinatorial solving, but it is difficult to be sure it is implemented correctly. The most successful approach to deal with bugs…

cs.AI2022★ 15 cited

Certified Symmetry and Dominance Breaking for Combinatorial Optimisation

Bart Bogaerts, Stephan Gocht, Ciaran McCreesh +1

Symmetry and dominance breaking can be crucial for solving hard combinatorial search and optimisation problems, but the correctness of these techniques sometimes relies on subtle a…

cs.AI2018

A Review of Literature on Parallel Constraint Solving

Ian P. Gent, Ciaran McCreesh, Ian Miguel +4

As multicore computing is now standard, it seems irresponsible for constraints researchers to ignore the implications of it. Researchers need to address a number of issues to explo…

cs.DC2017★ 19 cited

Replicable Parallel Branch and Bound Search

Blair Archibald, Patrick Maier, Ciaran McCreesh +2

Combinatorial branch and bound searches are a common technique for solving global optimisation and decision problems. Their performance often depends on good search order heuristic…

cs.CE2014★ 8 cited

Case Studies and Challenges in Reproducibility in the Computational Sciences

Sylwester Arabas, Michael R. Bareford, Lakshitha R. de Silva +14

This paper investigates the reproducibility of computational science research and identifies key challenges facing the community today. It is the result of the First Summer School…