Hybrid Optimization Algorithm Based on Wolf Pack Search and Local Search for Solving Traveling Salesman Problem
Author:
Publisher
Springer Science and Business Media LLC
Subject
Multidisciplinary
Link
http://link.springer.com/article/10.1007/s12204-019-2039-9/fulltext.html
Reference19 articles.
1. LAPOTE G. The traveling salesman problem: An overview of exact and approximate algorithms [J]. European Journal of Operational Research, 1992, 59(2): 231–247.
2. JIANG H, SUN W C, REN Z L, et al. Evolving hard and easy traveling salesman problem instances: A multi-objective approach [C]//Proceedings of the 10th International Conference on Simulated Evolution and Learning. Dunedin, New Zealand: Springer International Publishing, 2014: 216–227.
3. URRUTIA S, MILANÉS A, LØKKETANGEN A. A dynamic programming based local search approach for the double traveling salesman problem with multiple stacks [J]. International Transactions in Operational Research, 2015, 22(1): 61–75.
4. JOZEFOWIEZ N, LAPORTE G, SEMET F. A generic branch-and-cut algorithm for multiobjective optimization problems: Application to the multilabel traveling salesman problem [J]. INFORMS Journal on Computing, 2012, 24(4): 554–564.
5. QU D P, TU H, FAN T S. Performance analysis of local optimization algorithms in traveling salesman problem [J]. Advanced Materials Research, 2014, 846/847: 1364–1367.
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