Genetic algorithms for communications network design - An empirical study of the factors that influence performance

IEEE Transactions on Evolutionary Computation

Volumn 5, Issue 3, 2001, Pages 236-249

  Chou, Hsinghua ^a   Premkumar, G ^b   Chu, Chao Hsien ^c  

^a SPRINT NEXTEL   (United States)

^b IOWA STATE UNIVERSITY   (United States)

^c PENNSYLVANIA STATE UNIVERSITY   (United States)

Author keywords

Degree constrained minimum spanning tree; GA operators; Genetic algorithms; Network design

Indexed keywords

COMPUTATIONAL METHODS; GENETIC ALGORITHMS; HEURISTIC METHODS; OPTIMIZATION; PROBLEM SOLVING;

DEGREE CONSTRAINED MINIMUM SPANNING TREE (DCMST); NETWORK DESIGN;

TELECOMMUNICATION NETWORKS;

EID: 0035364338     PISSN: 1089778X     EISSN: None     Source Type: Journal    
DOI: 10.1109/4235.930313     Document Type: Article

References (50)

1. When genetic algorithms work best
2. Adapting operator probabilities in genetic algorithms
3. Genetic algorithms for the operations researcher
4. Optimization of control parameters for genetic algorithms
5. Local search genetic algorithm for optimal design of reliable networks
6. Global properties of evolution processes
7. Simulation of biological evolution and machine learning: I. Selection of self-reproducing numeric patterns by data processing machines, effects of hereditary control, mutation type, and crossing
8. Uniform crossover in genetic algorithms
9. Alleles loci and the traveling salesman problem
10. Genetic search with approximate function evaluations
11. Bin packing with adaptive search
12. Multilevel credit assignment in a genetic learning system
13. Genetic algorithm crossover operators for ordering applications
14. Determinant factorization: Anew encoding scheme for spanning trees applied to the probabilistic minimum spanning tree problem
15. Improving search in genetic algorithm
16. Developing fitter genetic algorithms
17. No free lunch theorems for optimization
18. Degree-constrained minimum spanning tree
19. On the history of minimum spanning tree problem
20. On the shortest spanning subtree of a graph and the traveling salesman problem
21. Shortest connection networks and some generalizations
22. Node fault tolerance in graphs
23. Optimally edge fault-tolerant trees
24. The NP-completeness column: An ongoing guide
25. Spanning tree manipulation and the travelling-salesman problem
26. Edge exchanges in the degree-constrained spanning tree problem
27. Genetic algorithms and communication link speed design: Constraints and operators
28. Solving the graphical Steiner tree problem using genetic algorithms
29. A genetic algorithm for channel assignment problems
30. Concentrator location-problems using genetic algorithms
31. An approach to a problem in network design using genetic algorithms
32. Computing near-optimal solutions to the Steiner problem in a graph using genetic algorithm
33. Applications of genetic algorithms in telecommunications
34. A note in genetic algorithms for degree constrained spanning tree problems
35. Encoding graph for genetic algorithms: An investigation using the minimum spanning tree problem
36. Neuer beweis eines satzes uber permutation
37. Genetic algorithms for flow shop sequencing
38. Adaptive penalty methods for genetic optimization of constrained combinatorial problems
39. Adaptive selection methods for genetic algorithms
40. Extended selection mechanism in genetic algorithms
41. Using Tabu search to solve the Steiner tree-star problem in telecommunication networks design
42. On the use of nonstationery penalty functions to solve nonlinear constrained optimization problems with GAs
43. Evolutionary algorithms for constrained parameter optimization problems
44. Varying fitness functions in genetic algorithm constrained optimization: The cutting stock and unit commitment problems