Travelling salesman problem solved ‘in materio’ by evolved carbon nanotube device

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8672, Issue , 2014, Pages 692-701

  Clegg, Kester Dean ^a   Miller, Julian Francis ^a   Massey, Kieran ^b   Petty, Mike ^b  

^a UNIVERSITY OF YORK   (United Kingdom)

^b DURHAM UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL EFFICIENCY; ELECTRODES; EVOLUTIONARY ALGORITHMS; HYBRID MATERIALS; HYBRID SYSTEMS; LEARNING ALGORITHMS; NANOTUBES; SINGLE-WALLED CARBON NANOTUBES (SWCN); CARBON NANOTUBES; COMPOSITE MATERIALS; TRAVELING SALESMAN PROBLEM; YARN;

CARBON NANOTUBE DEVICES; EVOLUTIONARY SEARCH ALGORITHMS; HYBRID COMPUTATION; MICROELECTRODE ARRAY; SEARCH PERFORMANCE; SINGLEWALLED CARBON NANOTUBE (SWCNT); TRAVELLING SALESMAN PROBLEM; TRAVELLING SALESMAN PROBLEM (TSP); POLYMER COMPOSITE MATERIALS;

TRAVELING SALESMAN PROBLEM; PROBLEM SOLVING;

EID: 84912115927     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-10762-2_68     Document Type: Article

References (25)

1. Walker, J., Trefzer, M., Bale, S., Tyrrell, A.: Panda: A reconfigurable architecture that adapts to physical substrate variations. IEEE Transactions on Computers 62(8), 1584–1596 (2013)
2. Walker, J.A., Trefzer, M.A., Tyrrell, A.M.: Designing function configuration decoders for the PAnDA architecture using multi-objective cartesian genetic programming. In: Suganthan, P.N. (ed.) 2013 IEEE Symposium Series on Computational Intelligence, Singapore, April 16-19, pp. 96–103 (2013)
3. Broersma, H., Gomez, F., Miller, J.F., Petty, M., Tufte, G.: Nascence project: Nanoscale engineering for novel computation using evolution. International Journal of Unconventional Computing 8(4), 313–317 (2012)
4. Graham, A.P., Duesberg, G.S., Hoenlein, W., Kreupl, F., Liebau, M., Martin, R., Rajasekharan, B., Pamler, W., Seidel, R., Steinhoegl, W., Unger, E.: How do carbon nanotubes fit into the semiconductor roadmap? Applied Physics A 80(6), 1141–1151 (2005)
5. Harding, S., Miller, J.F.: Evolution in materio: Evolving logic gates in liquid crystal. International Journal of Unconventional Computing 3(4), 243–257 (2007)
6. Thompson, A.: Evolving electronic robot controllers that exploit hardware resources. In: Morán, F., Merelo, J.J., Moreno, A., Chacon, P. (eds.) ECAL 1995. LNCS, vol. 929, pp. 640–656. Springer, Heidelberg (1995)
7. Miller, J.F., Harding, S.L., Tufte, G.: Evolution-in-materio: evolving computation in materials. Evolutionary Intelligence 7, 49–67 (2014)
8. Mills, J.W.: Polymer processors, tech. rep. tr580. Technical report, Department of Computer Science, University of Indiana (1995)
9. Harding, S., Miller, J.F.: Evolution in materio: Investigating the stability of robot controllers evolved in liquid crystal. In: Moreno, J.M., Madrenas, J., Cosp, J. (eds.) ICES 2005. LNCS, vol. 3637, pp. 155–164. Springer, Heidelberg (2005)
10. Thompson, A.: Evolving fault tolerant systems. In: Proc. 1st IEE/IEEE Int. Conf. on Genetic Algorithms in Engineering Systems: Innovations and Applications (GALESIA 1995), IEE Conf. Publication No. 414, pp. 524–529 (1995)
11. Harding, S., Miller, J.: Evolution in materio: a tone discriminator in liquid crystal. In: Congress on Evolutionary Computation, CEC 2004, vol. 2, pp. 1800–1807 (June 2004)
12. Adleman,L.M. .:Molecular computation of solutions to combinatorial problems. Science 266 (5187), 1021–1024 (1994)
13. Adamatzky, A.: Reaction-Diffusion Automata: Phenomenology, Localisations, Computation. Springer, Heidelberg (2013)
14. Thompson, A.: Exploring beyond the scope of human design: Automatic generation of FPGA configurations through artificial evolution (Keynote). In: Proc. 8th Annual Advanced PLD & FPGA Conference, Miller Freeman, pp. 5–8 (1998)
15. Harding, S.L., Miller, J.F., Rietman, E.A.: Evolution in materio: Exploiting the physics of materials for computation. International Journal of Unconventional Computing 4(2), 155–194 (2008)
16. Reinelt, G.: The Traveling Salesman. LNCS, vol. 840. Springer, Heidelberg (1994)
17. Fatih Tasgetiren, M., Sevkli, M., Yun-Chia, L., Gencyilmaz, G.: Particle swarm optimization algorithm for single machine total weighted tardiness problem. In: Congress on Evolutionary Computation, CEC 2004, vol. 2, pp. 1412–1419 (2004)
18. Tasgetiren, F., Chen, A., Gencyilmaz, G., Gattoufi, S.: Smallest position value approach. In: Onwubolu, G.C., Davendra, D. (eds.) Differential Evolution: A Handbook for Global Permutation-Based Combinatorial Optimization. SCI, vol. 175, pp. 121–138. Springer, Heidelberg (2009)
19. Rechenberg, I.: Evolutionsstrategie: Optimierung technischer Systeme nach Prinzipien der biologischen Evolution. Frommann-Holzbog (1973)
20. Schwefel, H.P.: Numerical optimization of Computer models. John Wiley & Sons, Ltd. (1981)
21. Beyer, H.G., Schwefel, H.P., Wegener, I.: How to analyse evolutionary algorithms. Theoretical Computer Science 287(1), 101–130 (2002)
22. Miller, J.F.: Cartesian Genetic Programming. Springer (2011)
23. Miller, J.F., Mohid, M.: Function optimization using Cartesian Genetic Programming. In: Proc. Conf. on Genetic and Evolutionary Computation (Companion), pp. 147–148 (2013)
24. Walker, J., Miller, J.F.: The automatic acquisition, evolution and re-use of modules in Cartesian genetic programming. IEEE Transactions on Evolutionary Computation 12, 397–417 (2008)
25. Thompson, A.: An Evolved Circuit, Intrinsic in Silicon, Entwined with Physics. In: Higuchi, T., Iwata, M., Weixin, L. (eds.) ICES 1996. LNCS, vol. 1259, pp. 390–405. Springer, Heidelberg (1997)