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Items: 1 to 20 of 120

1.

Combinatorial optimization with use of guided evolutionary simulated annealing.

Yip PC, Pao YH.

IEEE Trans Neural Netw. 1995;6(2):290-5.

PMID:
18263313
2.

An impatient evolutionary algorithm with probabilistic tabu search for unified solution of some NP-hard problems in graph and set theory via clique finding.

Guturu P, Dantu R.

IEEE Trans Syst Man Cybern B Cybern. 2008 Jun;38(3):645-66. doi: 10.1109/TSMCB.2008.915645.

PMID:
18558530
3.

A noisy chaotic neural network for solving combinatorial optimization problems: stochastic chaotic simulated annealing.

Wang L, Li S, Tian F, Fu X.

IEEE Trans Syst Man Cybern B Cybern. 2004 Oct;34(5):2119-25.

PMID:
15503507
5.

Ant system: optimization by a colony of cooperating agents.

Dorigo M, Maniezzo V, Colorni A.

IEEE Trans Syst Man Cybern B Cybern. 1996;26(1):29-41.

PMID:
18263004
6.

A Case Study of Controlling Crossover in a Selection Hyper-heuristic Framework Using the Multidimensional Knapsack Problem.

Drake JH, Özcan E, Burke EK.

Evol Comput. 2016 Spring;24(1):113-41. doi: 10.1162/EVCO_a_00145. Epub 2015 Jan 30.

PMID:
25635698
7.

Colored Traveling Salesman Problem.

Li J, Zhou M, Sun Q, Dai X, Yu X.

IEEE Trans Cybern. 2015 Nov;45(11):2390-401. doi: 10.1109/TCYB.2014.2371918. Epub 2014 Dec 4.

PMID:
25494521
8.

Chaotic Potts Spin Model for Combinatorial Optimization Problems.

Sato M, Ishii S.

Neural Netw. 1997 Jul;10(5):941-963.

PMID:
12662881
9.

Solving the quadratic assignment problem with clues from nature.

Nissen V.

IEEE Trans Neural Netw. 1994;5(1):66-72.

PMID:
18267780
10.

An adaptive evolutionary multi-objective approach based on simulated annealing.

Li H, Landa-Silva D.

Evol Comput. 2011 Winter;19(4):561-95. doi: 10.1162/EVCO_a_00038. Epub 2011 Jul 25.

PMID:
21417745
11.

Scheduling multiprocessor job with resource and timing constraints using neural networks.

Huang YM, Chen RM.

IEEE Trans Syst Man Cybern B Cybern. 1999;29(4):490-502. doi: 10.1109/3477.775265.

PMID:
18252324
12.

A Discrete Fruit Fly Optimization Algorithm for the Traveling Salesman Problem.

Jiang ZB, Yang Q.

PLoS One. 2016 Nov 3;11(11):e0165804. doi: 10.1371/journal.pone.0165804. eCollection 2016.

13.

Hybridization of decomposition and local search for multiobjective optimization.

Ke L, Zhang Q, Battiti R.

IEEE Trans Cybern. 2014 Oct;44(10):1808-20. doi: 10.1109/TCYB.2013.2295886.

PMID:
25222724
14.

A genetic algorithm-based approach to flexible flow-line scheduling with variable lot sizes.

Lee I, Sikora R, Shaw MJ.

IEEE Trans Syst Man Cybern B Cybern. 1997;27(1):36-54.

PMID:
18255838
15.

A medical diagnostic tool based on radial basis function classifiers and evolutionary simulated annealing.

Alexandridis A, Chondrodima E.

J Biomed Inform. 2014 Jun;49:61-72. doi: 10.1016/j.jbi.2014.03.008. Epub 2014 Mar 21.

16.

An evolutionary algorithm for large traveling salesman problems.

Tsai HK, Yang JM, Tsai YF, Kao CY.

IEEE Trans Syst Man Cybern B Cybern. 2004 Aug;34(4):1718-29.

PMID:
15462439
17.

Optimization by quantum annealing: lessons from hard satisfiability problems.

Battaglia DA, Santoro GE, Tosatti E.

Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Jun;71(6 Pt 2):066707. Epub 2005 Jun 29.

PMID:
16089911
18.

Solving the multiple competitive facilities location and design problem on the plane.

Redondo JL, Fernández J, García I, Ortigosa PM.

Evol Comput. 2009 Spring;17(1):21-53. doi: 10.1162/evco.2009.17.1.21.

PMID:
19207087
19.

A Kohonen-like decomposition method for the Euclidean traveling salesman problem-KNIES/spl I.bar/DECOMPOSE.

Aras N, Altinel IK, Oommen J.

IEEE Trans Neural Netw. 2003;14(4):869-90. doi: 10.1109/TNN.2003.811562.

PMID:
18238067
20.

Automatic Combination of Operators in a Genetic Algorithm to Solve the Traveling Salesman Problem.

Contreras-Bolton C, Parada V.

PLoS One. 2015 Sep 14;10(9):e0137724. doi: 10.1371/journal.pone.0137724. eCollection 2015.

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