The time complexity of maximum matching by simulated annealing
Journal of the ACM (JACM)
The effect of the density of states on the Metropolis algorithm
Information Processing Letters
The Markov chain Monte Carlo method: an approach to approximate counting and integration
Approximation algorithms for NP-hard problems
The metropolis algorithm for graph bisection
Discrete Applied Mathematics
Evolutionary Algorithms and the Maximum Matching Problem
STACS '03 Proceedings of the 20th Annual Symposium on Theoretical Aspects of Computer Science
Randomized local search, evolutionary algorithms, and the minimum spanning tree problem
Theoretical Computer Science
Simulated annealing for graph bisection
SFCS '93 Proceedings of the 1993 IEEE 34th Annual Foundations of Computer Science
On the local performance of simulated annealing and the (1+1) evolutionary algorithm
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Maximum cardinality matchings on trees by randomized local search
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Simulated Annealing versus Metropolis for a TSP instance
Information Processing Letters
Theoretical Computer Science
Crossover can provably be useful in evolutionary computation
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Memetic algorithms with variable-depth search to overcome local optima
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Simulated annealing, its parameter settings and the longest common subsequence problem
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Ant Colony Optimization and the Minimum Spanning Tree Problem
Learning and Intelligent Optimization
Why standard particle swarm optimisers elude a theoretical runtime analysis
Proceedings of the tenth ACM SIGEVO workshop on Foundations of genetic algorithms
Greedy Local Search and Vertex Cover in Sparse Random Graphs
TAMC '09 Proceedings of the 6th Annual Conference on Theory and Applications of Models of Computation
Runtime analysis of an ant colony optimization algorithm for TSP instances
IEEE Transactions on Evolutionary Computation
Ant Colony Optimization and the minimum spanning tree problem
Theoretical Computer Science
Analysis of computational time of simple estimation of distribution algorithms
IEEE Transactions on Evolutionary Computation
Necessary and sufficient conditions for success of the metropolis algorithm for optimization
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Crossover can provably be useful in evolutionary computation
Theoretical Computer Science
Analysis of an iterated local search algorithm for vertex cover in sparse random graphs
Theoretical Computer Science
Runtime analysis of a simple ant colony optimization algorithm
ISAAC'06 Proceedings of the 17th international conference on Algorithms and Computation
The use of tail inequalities on the probable computational time of randomized search heuristics
Theoretical Computer Science
Annals of Mathematics and Artificial Intelligence
| Hi-index | 0.01 |
The Metropolis algorithm is simulated annealing with a fixed temperature. Surprisingly enough, many problems cannot be solved more efficiently by simulated annealing than by the Metropolis algorithm with the best temperature. The problem of finding a natural example (artificial examples are known) where simulated annealing outperforms the Metropolis algorithm for all temperatures has been discussed by Jerrum and Sinclair (1996) as “an outstanding open problem.” This problem is solved here. The examples are instances of the well-known minimum spanning tree problem. Moreover, it is investigated which instances of the minimum spanning tree problem can be solved efficiently by simulated annealing. This is motivated by the aim to develop further methods to analyze the simulated annealing process.