A Memetic Algorithm To Find a Hamiltonian Cycle in a Hamiltonian Graph
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Abstract (arXiv)
We present a memetic algorithm (maa) approach for finding a Hamiltonian cycle in a Hamiltonian graph. The ma is based on a proven approach to the Asymmetric Travelling Salesman Problem (atspp) that, in this contribution, is boosted by the introduction of more powerful local searches. Our approach also introduces a novel technique that sparsifies the input graph under consideration for Hamiltonicity and dynamically augments it during the search. Such a combined heuristic approach helps to prove Hamiltonicity by finding a Hamiltonian cycle in less time. In addition, we also employ a recently introduced polynomial-time reduction from the hamcyc to the Symmetric tsp, which is based on computing the transitive closure of the graph. Although our approach is a metaheuristic, i.e., it does not give a theoretical guarantee for finding a Hamiltonian cycle, we have observed that the method is successful in practice in verifying the Hamiltonicity of a larger number of instances from the textitFlinder University Hamiltonian Cycle Problem Challenge Set (fhcpsc), even for the graphs that have large treewidth. The experiments on the fhcpscc instances and a computational comparison with five recent state-of-the-art baseline approaches show that the proposed method outperforms those for the majority of the instances in the fhcpsc.
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References · 4
- 2016Neural Combinatorial Optimization with Reinforcement Learningcited by 608
- 2018Reinforcement Learning for Solving the Vehicle Routing Problemcited by 333
- 2017Learning to Optimize Neural Netscited by 41
- 2018Finding Hamiltonian Cycle in Graphs of Bounded Treewidth: Experimental Evaluationcited by 2
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