Abstract
We consider a new class of optimization heuristics which combine local searches with stochastic sampling methods, allowing one to iterate local optimization heuristics. We have tested this on the Euclidean Traveling Salesman Problem, improving 3-opt by over 1.6% and Lin-Kernighan by 1.3%.
Original language | English (US) |
---|---|
Pages (from-to) | 219-224 |
Number of pages | 6 |
Journal | Operations Research Letters |
Volume | 11 |
Issue number | 4 |
DOIs | |
State | Published - May 1992 |
All Science Journal Classification (ASJC) codes
- Software
- Management Science and Operations Research
- Industrial and Manufacturing Engineering
- Applied Mathematics
Keywords
- Markov
- TSP
- optimization
- simulated annealing