New results in the packing of equal circles in a square
Discrete Mathematics
Packing equal circles in a square: a deterministic global optimization approach
Discrete Applied Mathematics
Approximate algorithms for constrained circular cutting problems
Computers and Operations Research
A New Verified Optimization Technique for the "Packing Circles in a Unit Square" Problems
SIAM Journal on Optimization
Handbook of Combinatorial Designs, Second Edition (Discrete Mathematics and Its Applications)
Handbook of Combinatorial Designs, Second Edition (Discrete Mathematics and Its Applications)
New Approaches to Circle Packing in a Square: With Program Codes (Springer Optimization and Its Applications)
Journal of Computational and Applied Mathematics - Special issue: Scientific computing, computer arithmetic, and validated numerics (SCAN 2004)
Computers and Operations Research
The optimal design of sheet metal forming processes: application to the clinching of thin sheets
International Journal of Computer Applications in Technology
Some practical solutions to the uncertainties of the ant colony optimisation
International Journal of Computer Applications in Technology
Multi-agent simulated annealing algorithm based on particle swarm optimisation algorithm
International Journal of Computer Applications in Technology
Greedy vacancy search algorithm for packing equal circles in a square
Operations Research Letters
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Seeking an improbable, but globally optimum, state is useful in many scientific and engineering endeavours. To handle a larger data size, computational techniques are often employed. Yet, they are bound by the inherent combinatorial complexity. This paper employs the examples of packing a set of circles into a square to verify the existence of the pathways between the global optimisations based on the hypothesis that hopping from one known optimum to an unknown optimum in a global landscape is feasible. Twenty seven proven optimal circle packing configurations are investigated and eleven pathways are identified. These pathways lead to other optimal configurations which conform to the best known results. These pathways are beneficial to obtaining the optimum since it does not require going through the combinatorial many intermediate configuration before reaching the optimum.