Towards practical `neural' computation for combinatorial optimization problems
AIP Conference Proceedings 151 on Neural Networks for Computing
K-d trees for semidynamic point sets
SCG '90 Proceedings of the sixth annual symposium on Computational geometry
Modern heuristic techniques for combinatorial problems
Intelligence through simulated evolution: forty years of evolutionary programming
Intelligence through simulated evolution: forty years of evolutionary programming
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Genetic Local Search Algorithms for the Travelling Salesman Problem
PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
Local Optimization and the Traveling Salesman Problem
ICALP '90 Proceedings of the 17th International Colloquium on Automata, Languages and Programming
Finding Cuts in the TSP (A preliminary report)
Finding Cuts in the TSP (A preliminary report)
A new iterated local search algorithm using genetic crossover for the traveling salesman problem
Proceedings of the 1999 ACM symposium on Applied computing
Design of Iterated Local Search Algorithms
Proceedings of the EvoWorkshops on Applications of Evolutionary Computing
Lock-Gain Based Graph Partitioning
Journal of Heuristics
Investigation of the Fitness Landscapes in Graph Bipartitioning: An Empirical Study
Journal of Heuristics
Embedded local search approaches for routing optimization
Computers and Operations Research
Routing-aware scan chain ordering
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Routing-aware scan chain ordering
ASP-DAC '03 Proceedings of the 2003 Asia and South Pacific Design Automation Conference
Stochastic local search for multiprocessor scheduling for minimum total tardiness
AI'03 Proceedings of the 16th Canadian society for computational studies of intelligence conference on Advances in artificial intelligence
Match twice and stitch: a new TSP tour construction heuristic
Operations Research Letters
Parallel GPU implementation of iterated local search for the travelling salesman problem
LION'12 Proceedings of the 6th international conference on Learning and Intelligent Optimization
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The large-step Markov chain (LSMC) approach is the mosteffective known heuristic for large symmetric TSP instances; cf.recent results of [Martin, Otto and Felten, 1991] and [Johnson,1990]. In this paper, we examine relationships among (i) theunderlying local optimization engine within the LSMC approach, (ii)the “kick move” perturbation that is applied between successivelocal search descents, and (iii) the resulting LSMC solutionquality. We find that the traditional “double-bridge” kick move isnot necessarily optimum: stronger local optimization engines (e.g.,Lin-Kernighan) are best matched with stronger kick moves. We alsopropose use of an adaptive temperature schedule to allow escape fromdeep basins of attraction; the resulting hierarchical LSMCvariant outperforms traditional LSMC implementations that useuniformly zero temperatures. Finally, a population-based LSMCvariant is studied, wherein multiple solution paths can interact toachieve improved solution quality.