An enhanced hybrid genetic algorithm for solving traveling salesman problem
Robust known the exceedingly famed NP-hard problem in combinatorial optimization is the Traveling Salesman Problem (TSP), promoting the skillful algorithms to get the solution of TSP have been the burden for several scholars. For inquiring global optimal solution, the presented algorithm hybridizes...
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| Format: | EJournal Article |
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Institute of Advanced Engineering and Science,
2020-05-01.
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| Online Access: | Get fulltext |
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| LEADER | 02220 am a22003133u 4500 | ||
|---|---|---|---|
| 001 | ijeecs20583_13702 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Ali, Zeravan Arif |e author |
| 100 | 1 | 0 | |e contributor |
| 700 | 1 | 0 | |a Rasheed, Subhi Ahmed |e author |
| 700 | 1 | 0 | |a Ali, Nabeel No'man |e author |
| 245 | 0 | 0 | |a An enhanced hybrid genetic algorithm for solving traveling salesman problem |
| 260 | |b Institute of Advanced Engineering and Science, |c 2020-05-01. | ||
| 500 | |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/20583 | ||
| 520 | |a Robust known the exceedingly famed NP-hard problem in combinatorial optimization is the Traveling Salesman Problem (TSP), promoting the skillful algorithms to get the solution of TSP have been the burden for several scholars. For inquiring global optimal solution, the presented algorithm hybridizes genetic and local search algorithm to take out the uplifted quality results. The genetic algorithm gives the best individual of population by enhancing both cross over and mutation operators while local search gives the best local solutions by testing all neighbor solution. By comparing with the conventional genetic algorithm, the numerical outcomes acts that the presented algorithm is more adequate to attain optimal or very near to it. Problems arrested from the TSP library strongly trial the algorithm and shows that the proposed algorithm can reap outcomes within reach optimal. For more details, please download TEMPLATE HELP FILE from the website. | ||
| 540 | |a Copyright (c) 2020 Institute of Advanced Engineering and Science | ||
| 540 | |a http://creativecommons.org/licenses/by-nc/4.0 | ||
| 546 | |a eng | ||
| 690 | |||
| 690 | |a Genetic Algorithm; Local Search; TSP | ||
| 655 | 7 | |a info:eu-repo/semantics/article |2 local | |
| 655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
| 655 | 7 | |2 local | |
| 786 | 0 | |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 18, No 2: May 2020; 1035-1039 | |
| 786 | 0 | |n 2502-4760 | |
| 786 | 0 | |n 2502-4752 | |
| 786 | 0 | |n 10.11591/ijeecs.v18.i2 | |
| 787 | 0 | |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/20583/13702 | |
| 856 | 4 | 1 | |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/20583/13702 |z Get fulltext |