[1]

Kwong W. C., Yang G. C., An algebraic approach to the unequal–spaced channel–allocation problem in WDM lightwave systems, IEEE Trans. Commun., 1997, 45(3), 352-359. CrossrefGoogle Scholar

[2]

Chraplyvy A. R., Limitations on lightwave communications imposed by optical–fiber nonlinearities, J. Lightwave Technol., 1990, 8, 1548-1557.CrossrefGoogle Scholar

[3]

Aggarwal G. P., Nonlinear fiber optics, 2nd ed., Academic Press, San Diego, CA, 2001. Google Scholar

[4]

Thing V. L. L., Shum P., Rao M. K., Bandwidth–efficient WDM channel allocation for four–wave mixing–effect minimization, IEEE Trans. Commun., 2004, 52(2.12), 2184-2189.CrossrefGoogle Scholar

[5]

Saaid N. M., Nonlinear optical effects suppression methods in WDM systems with EDFAs: A review, Proceedings of International Conference on Computer and Communication Engineering (ICCCE-2010, May-2010, Kuala Lumpur, Malaysia), 2010.Google Scholar

[6]

Forghieri F., R. Tkach W., Chraplyvy A. R., Marcuse D., Reduction of four–wave mixing crosstalk in WDM systems using unequally spaced channels, IEEE Photon. Technol. Lett., 1994, 6(6), 754-756.CrossrefGoogle Scholar

[7]

Babcock W., Intermodulation Interference in Radio Systems, Bell Syst. Tech. J., 1953, 63-73. Google Scholar

[8]

Sugumaran S., Sharma N., Chitranshi S., Thakur N., Arulmozhivarman P., Effect of four–wave mixing on WDM system and its suppression using optimum algorithms, Int. J. Engineer. Technol. (IJET), 2013, 5(2), 1432-1444.Google Scholar

[9]

Singh K., Bansal S., Suppression of FWM crosstalk on WDM systems using unequally spaced channel algorithms–A survey, Int. J. Advan. Res. Comput. Sci. Soft. Eng. (IJARCSSE), 2013, 3(12), 25-31. Google Scholar

[10]

Sardesai H. P., A simple channel plan to reduce effects of nonlinearities in dense WDM systems, Lasers and Electro–Optics, (23-28 May 1999, CLEO ‘99 Baltimore, MD, USA), 1999, 183-184, DOI: 10.1109/CLEO.1999.834058. Google Scholar

[11]

Forghieri F., Tkach R. W., Chraplyvy A. R., WDM systems with unequally spaced channels, J. Lightwave Technol., 1995, 13, 889-897.CrossrefGoogle Scholar

[12]

Hwang B., Tonguz O. K., A generalized suboptimum unequally spaced channel allocation technique—Part I: In IM/DDWDM systems, IEEE Trans. Commun., 1998, 46, 1027-1037.CrossrefGoogle Scholar

[13]

Tonguz O. K., Hwang B., A generalized suboptimum unequally spaced channel allocation technique—Part II: In coherent WDM systems,” IEEE Trans. Commun., 1998, 46, 1186-1193.CrossrefGoogle Scholar

[14]

Atkinson M. D., Santoro N., Urrutia J., Integer sets with distinct sums and differences and carrier frequency assignments for nonlinear repeaters, IEEE Trans. Commun., 1986, 34(6), 614-617.CrossrefGoogle Scholar

[15]

Randhawa R., Sohal J. S., Kaler R. S., Optimum algorithm for WDM channel allocation for reducing four–wave mixing effects, Optik 120, 2009, 898-904. Google Scholar

[16]

http://www.compunity.org/events/pastevents/ewomp2004/jaillet_krajecki_pap_ew04.pdf.

[17]

Bloom G. S., Golomb S. W., Applications of numbered undirected graphs, Proc. IEEE, 1977, 65(4), 562-570. CrossrefGoogle Scholar

[18]

Thing V. L. L, Rao M. K., Shum P., Fractional optimal Golomb ruler based WDM channel allocation, Proceedings of The 8th Opto–Electronics and Communication Conference (OECC-2003, October-2003), 2003, 23, 631-632.Google Scholar

[19]

Shearer J. B., Some new disjoint Golomb rulers, IEEE Trans. Inf. Theory, 1998, 44(7), 3151-3153. CrossrefGoogle Scholar

[20]

http://theinf1.informatik.uni-jena.de/teaching/ss10/oberseminar-ss10.

[21]

Robinson J. P., Optimum Golomb rulers, IEEE Trans. Comput., 1979, 28(12), 183-184. Google Scholar

[22]

Shearer J. B., Some new optimum Golomb rulers, IEEE Trans Inf. Theory, 1990, 36, 183-184. CrossrefGoogle Scholar

[23]

Galinier P., Jaumard B., Morales R., Pesant G., A constraint–based approach to the Golomb ruler problem, Proceedings of 3rd International Workshop on Integration of AI and OR Techniques (CP–AI-OR 2001), 2001.Google Scholar

[24]

Leitao T., Evolving the maximum segment length of a Golomb ruler, Proceedings of Genetic and Evolutionary Computation Conference (June-2004, USA), 2004.Google Scholar

[25]

Rankin W. T., Optimal Golomb rulers: An exhaustive parallel search implementation, M.S. Thesis, Duke University, 1993, http://people.ee.duke.edu/~wrankin/golomb/golomb.html.

[26]

Cotta C., Dotú I., Fernández A. J., Hentenryck P. V., A memetic approach to Golomb rulers, parallel problem solving from nature–PPSN IX, Lecture Notes in Computer Science, Springer–Verlag Berlin Heidelberg, 2006, 4193, 252-261. Google Scholar

[27]

Soliday S. W., Homaifar A., Lebby G. L., Genetic algorithm approach to the search for Golomb rulers, Proceedings of the Sixth International Conference on Genetic Algorithms (ICGA-95, Morgan Kaufmann), 1995, 528-535. Google Scholar

[28]

Robinson J. P., Genetic search for Golomb arrays, IEEE Trans Inf. Theory, 2000, 46(3), 1170-1173.CrossrefGoogle Scholar

[29]

Ayari N., Luong T. V., Jemai A., A hybrid genetic algorithm for Golomb ruler problem, Proceedings of ACS/IEEE International Conference on Computer Systems and Applications (AICCSA-2010, May 16-19, 2010), 2010, 1-4. Google Scholar

[30]

Bansal S., Optimal Golomb ruler sequence generation for FWM crosstalk elimination: Soft computing versus conventional approaches”, Appl. Soft Comput., 2014, 22, 443-457. CrossrefGoogle Scholar

[31]

Bansal S., Kumar S., Sharma H., P. Bhalla, Golomb ruler sequences optimization: A BBO approach, Int. J. Comput. Sci. Inf. Secur. (IJCSIS), 2011, 9(5), 63-71. Google Scholar

[32]

Bansal S., Golomb ruler sequences optimization: Soft computing approaches, M.Tech. Thesis, Maharishi Markandeshwar Engineering College, Deemed University, Mullana, India, 2011. Google Scholar

[33]

Kumar S., Bansal S., Bhalla P., Optimal Golomb ruler sequence generation for FWM crosstalk elimination: A BB–BC approach, Proceedings of 6th International Multi Conference on Intelligent Systems, Sustainable, New and Renewable Energy Technology and Nanotechnology (IISN–2012, March 16-18, 2012, Institute of Science and Technology Klawad, Haryana), India, 2012, 255-262. Google Scholar

[34]

Bansal S., Kumar S., Bhalla P., A novel approach to WDM channel allocation: Big bang–big crunch optimization, Proceedings of Zonal Seminar on Emerging Trends in Embedded System Technologies (ETECH-2013, The Institution of Electronics and Telecommunication Engineers (IETE), Chandigarh Centre, Chandigarh), India, 2013, 80-81. Google Scholar

[35]

Bali S., Bansal S., Kamboj A., A novel hybrid multi–objective BB–BC based channel allocation algorithm to reduce FWM crosstalk and its comparative study, Int. J. Comput. Appl. (IJCA), 2015, 124(12), 38-45.Google Scholar

[36]

Vyas J., Bansal S., Sharma K., Generation of optimal Golomb rulers for FWM crosstalk reduction: BB–BC and FA approaches, Proceedings of 2016 International Conference on Signal Processing and Communication (ICSC-2016, December 26-28, 2016), Jaypee Institute of Information Technology, Noida, India, 2016, 74-78. Google Scholar

[37]

Bansal S., Singh K., A novel soft–computing algorithm for channel allocation in WDM systems, Int. J. Comput. Appl. (IJCA), 2014, 85(9), 19-26. Google Scholar

[38]

Bansal S., Jain P., Singh A. K., Gupta N., Improved multi–objective firefly algorithms to find OGR sequences for WDM channel–allocation, World Academy of Science, Engineering and Technology, International Science Index, Int. J. Math., Comput., Phy., Elect. Comput. Eng., 2016, 10(7), 315-322. Google Scholar

[39]

Dotú I., Hentenryck P. V., A simple hybrid evolutionary algorithm for finding Golomb rulers, Proceedings of Evolutionary Computation, (2-5 September, 2005, The 2005 IEEE Congress on), 2005, 3, 2018-2023, DOI: 10.1109/CEC.2005.1554943. Google Scholar

[40]

Colannino J., Circular and modular Golomb rulers, 2003. http://cgm.cs.mcgill.ca/~athens/cs507/Projects/2003/JustinColannino/.

[41]

Dimitromanolakis A., Analysis of the Golomb ruler and the sidon set problems, and determination of large, near–optimal Golomb rulers, Master’s Thesis, Technical University of Crete, 2002. Google Scholar

[42]

Dollas A., Rankin W. T., McCracken D., A new algorithm for Golomb ruler derivation and proof of the 19 mark ruler, IEEE Trans. Inf. Theory, 1998, 44(1), 379-382. CrossrefGoogle Scholar

[43]

Distributed.net, Project OGR. http://www.distributed.net/ogr.

[44]

Cotta C, Dotú I., Fernandez A. J., Hentenryck P. V., Local search–based hybrid algorithms for finding Golomb rulers, Kluwer Academic Publishers, Boston, 2007, 12(3), 263-291. Google Scholar

[45]

Drakakis K., S. Rickard, On the construction of nearly optimal Golomb rulers by unwrapping costas arrays, Contemp. Eng. Sci., 2010, 3(7), 295-309. Google Scholar

[46]

Drakakis K., A review of the available construction methods for Golomb rulers, Adv. in Math. Commun., 2009, 3(3), 235-250. CrossrefGoogle Scholar

[47]

Caicedo Y., Martos C. A., Trujillo C. A., g–Golomb rulers, Revista Integración Temas Mat., 2015, 33(2), 161-172, DOI: http://dx.doi.org/10.18273/revint.v33n2-2015006.

[48]

http://mathworld.wolfram.com/PerfectRuler.html.

[49]

http://mathworld.wolfram.com/GolombRuler.html.

[50]

Lam A. W., Sarwate D. V., On optimal time–hopping patterns, IEEE Trans. Commun., 1988, 36, 380-382. CrossrefGoogle Scholar

[51]

Lavoie P., Haccoun D., Savaria Y., New VLSI architectures for fast soft–decision threshold decoders, IEEE Trans. Commun., 1991, 39(2), 200-207. CrossrefGoogle Scholar

[52]

Robinson J. P., Bernstein A. J., A class of binary recurrent codes with limited error propagation, IEEE Trans. Inf. Theory,1967, IT–13, 106-113.Google Scholar

[53]

Cotta C., Fernández A. J., Analyzing fitness landscapes for the optimal Golomb ruler problem, Evolutionary Computation in Combinatorial Optimization, (Eds. J. Gottlieb, G. Raidl), Lecture Notes in Computer Science, 2005, Springer–Verlag Berlin, 3448, 68-79.Google Scholar

[54]

Fang R. J. F., Sandrin W. A., Carrier frequency assignment for non–linear repeaters, Comsat Tech.l Rev., 1977, 7, 227-245.Google Scholar

[55]

Blum E. J., Biraud F., Ribes J. C, On optimal synthetic linear arrays with applications to radio astronomy, IEEE Trans. Antennas Propag., 1974, 22, 108-109.CrossrefGoogle Scholar

[56]

Memarsadegh N., Golomb patterns: Introduction, applications, and citizen science game, Information Science and Technology (IS&T), Seminar Series NASA GSFC, 11September, 2013. http://istcolloq.gsfc.nasa.gov/fall2013/presentations/memarsadeghi.pdf.

[57]

Shearer J. B., Golomb ruler table, Mathematics Department, IBM Research, http://www.research.ibm.com/people/s/shearer/grtab.html.

[58]

Shearer J. B., Smallest known Golomb rulers, Mathematics Department, IBM Research, http://www.research.ibm.com/people/s/shearer/gropt.html.

[59]

Dewdney A., Computer recreations, Scientific American, 1985, 16-26. Google Scholar

[60]

Dewdney A., Computer recreations, Scientific American, 1986, 14-21. Google Scholar

[61]

Cotta C., Hemert J. V., Recent advances in evolutionary computation for combinatorial optimization, Studies in Computational Intelligence, Springer, 153. Google Scholar

[62]

Yang X. S., Optimization and metaheuristic algorithms in engineering, in: Metaheursitics in Water, Geotechnical and Transport Engineering (Eds. X. S.Yang, A. H. Gandomi, S. Talatahari, A. H. Alavi), Elsevier, 2013, 1-23, http://dx.doi.org/10.1016/B978-0-12-398296-4.00001-5.

[63]

Yang X. S., Nature–inspired metaheuristic algorithms, 2nd Edition, Luniver Press, 2010.Google Scholar

[64]

Koziel S., Yang X. S., Computational optimization, methods and algorithms, Studies in Computational Intelligence, Springer, 2011, 356. Google Scholar

[65]

Yang X. S., Nature–inspired mateheuristic algorithms: success and new challenges, J. Comput. Eng. Inf. Tech. (JCEIT), 2012, 1(1), 1-3, doi:104172/2324-9307.1000e101. Google Scholar

[66]

Rajasekaran S., and Pai G. A. V, Neural networks, fuzzy logic, and genetic algorithms–synthesis and applications, Prentice Hall of India Pvt. Ltd., New Delhi, 2004.Google Scholar

[67]

Mitchell M., An introduction to genetic algorithms, Prentice Hall of India Pvt. Ltd., New Delhi, 2004.Google Scholar

[68]

Goldberg D. E., Genetic algorithms in search, optimization, and machine learning, Addison Wesley, USA, 1989. Google Scholar

[69]

Storn R., Price K. V., Differential evolution—A simple and efficient heuristic for global optimization over continuous spaces, J. Glob. Optim., 1997, 11(4), 341-359. CrossrefGoogle Scholar

[70]

Price K., Storn R., Lampinen J., Differential evolution–A practical approach to global optimization, Springer, Berlin, Germany, 2005. Google Scholar

[71]

Yang X. S., Flower pollination algorithm for global optimization, in: Unconventional Computation and Natural Computation 2012, Lecture Notes in Computer Science, Springer, Berlin, 2012, 7445, 240-249. Google Scholar

[72]

Yang X. S., Review of metaheuristics and generalized evolutionary walk algorithm, Int. J. Bio–Inspir. Comput., 2011, 3(2), 77–84. CrossrefGoogle Scholar

[73]

Yang X. S., A new metaheuristic bat–inspired algorithm, in: Nature Inspired Coop–erative Strategies for Optimization (NISCO-2010) (Eds. J. R. Gonzalez et al.), Studies in Computational Intelligence, Springer Berlin, 2010, 284, 65-74. Google Scholar

[74]

Yang X. S., Bat algorithm for multi–objective optimization, Int. J. Bio–Inspir. Comput., 2011, 3(5), 267-274. CrossrefGoogle Scholar

[75]

Yang X. S., Bat algorithm: literature review and applications, Int. J. Bio–Inspir. Comput., 2013, 5(3), 141-149, DOI: 10.1504/IJBIC.2013.055093.CrossrefGoogle Scholar

[76]

Yang X. S., Gandomi A. H., Bat algorithm: A novel approach for global engineering optimization, Eng. Comput., 2012, 29(5), 464-483. CrossrefGoogle Scholar

[77]

Yang X. S., Deb S., Engineering optimisation by cuckoo search, Int. J. Math. Model. Numer. Optim., 2010, 1(4), 330-343. Google Scholar

[78]

Yang X. S., Deb S., Cuckoo search via levy flights, in: Proc. of World Congress on Nature & Biologically Inspired Computing (NABIC-2009), IEEE Publications, USA, 2009, 210-214.Google Scholar

[79]

Gandomi A. H., Yang X. S., Alavi A. H., Cuckoo search algorithm: A metaheuristic approach to solve structural optimization problems, Eng. with Comput. An Int. J. Sim. Based Eng., Springer Verlang, London, 2013, 29(1), 17-35, DOI:10.1007/s00366- 011-0241-y.Google Scholar

[80]

Yang X. S., Deb S., Cuckoo search: recent advances and applications, Neural Computing and Applications, 2014, 24(1), 169-174. CrossrefGoogle Scholar

[81]

Yang X. S., Karamanoglu M., He. X. S., Multi–objective flower algorithm for optimization, Proceedings of International Conference on Computational Science (ICCS-2013, Procedia Computer Science), 2013, 18, 861-868. Google Scholar

[82]

Yang X. S., Karamanoglu M., He. X. S., Flower pollination algorithm: A novel approach for multiobjective optimization, Eng. Optim., 2014, 46(9), 1222-1237, DOI: 10.1080/0305215X.2013.832237. Google Scholar

[83]

Pratap R., Getting started with Matlab a quick introduction for scientists and engineers, Oxford University Press, New York, 2010. Google Scholar

[84]

http://www.myreaders.info/html/artificial_intelligence.html.

[85]

Derrac J., García S., Molina D., Herrera F., A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms, Swarm and Evolut. Comput., 2011, 1, 3-18. CrossrefGoogle Scholar

[86]

Holm S., A simple sequentially rejective multiple test procedure, Scand. J. Stat., 1979, 6, 65-70. Google Scholar

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