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Fuzzy hybrid simulated annealing algorithms for topology design of switched local area networks

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Abstract

Topology design of switched local area networks (SLAN) is classified as an NP-hard problem since a number of objectives, such as monetary cost, network delay, hop count between communicating pairs, and reliability need to be simultaneously optimized under a set of constraints. This paper presents a multiobjective heuristic based on a simulated annealing (SA) algorithm for topology design of SLAN. Fuzzy logic has been incorporated in the SA algorithm to handle the imprecise multiobjective nature of the SLAN topology design problem, since the logic provides a suitable mathematical framework to address the multiobjective aspects of the problem. To enhance the performance of the proposed fuzzy simulated annealing (FSA) algorithm, two variants of FSA are also proposed. These variants incorporate characteristics of tabu search (TS) and simulated evolution (SimE) algorithms. The three proposed fuzzy heuristics are mutually compared with each other. Furthermore, two fuzzy operators, namely, ordered weighted average (OWA) and unified AND–OR (UAO) are also applied in certain steps of these algorithms. Results show that in general, the variant which embeds characteristics of SimE and TS into the fuzzy SA algorithm exhibits more intelligent search of the solution subspace and was able to find better solutions than the other two variants of the fuzzy SA. Also, the OWA and UAO operators exhibited relatively similar performance.

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References

  • Aggarwal KK, Rai S (1981) Reliability evaluation in computer communication networks. IEEE Trans Reliab 30(1): 32–35

    Article  MATH  Google Scholar 

  • Ali M (2000) Assignment of multicast switches in optical networks. In: Proceedings of 25th annual IEEE conference on local computer networks, pp 381–382

  • Atiqullah MM, Rao SS (1993) Reliability optimization of communication networks using simulated annealing. Microelect Reliab 33(9): 1303–1319

    Article  Google Scholar 

  • Belegundu AD et al. (1994) Multi-objective optimization of laminated ceramic composites using genetic algorithms. In: Proceedings of the 5th AIAA/NASA/USAF/ISSMO symposium on multidiscipinary analysis and optimization, pp 1015–1022

  • Bordogna G, Fedrizzi M, Pasi G (1997) A linguistic modelling of consensus in group decision making based on OWA operators. IEEE Trans Syst Man Cybern Part A 27(1): 126–133

    Article  Google Scholar 

  • Cho H, Oh S, Choi D (1998) A new evolutionary programming approach based on simulated annealing with local cooling schedule. In: Proceedings of the IEEE world congress on computational intelligence, pp 598–602

  • Colorni A, Dorigo M, Maniezzo M (1991) Distributed optimization by ant colonies. In: Proceedings of European conference on artificial life. Elsevier, Amsterdam, pp 134–142

  • Demirkol I, Ersoy C, Caglayan MU, Delic H (2001) Location area planning in cellular networks using simulated annealing. In: Proceedings of IEEE INFOCOM, pp 13–20

  • Dengiz B, Alabas C (2001) A simulated annealing algorithm for design of computer communication networks. In: Proceedings of world multiconference on systemics, cybernetics, and informatics, pp 188–193

  • Dengiz B, Altiparmak F, Smith A (1997a) Efficient optimization of all—terminal reliable networks using an evolutionary approach. IEEE Trans Reliab 46: 18–25

    Article  Google Scholar 

  • Dengiz B, Altiparmak F, Smith A (1997b) Local search genetic algorithm for optimal design of reliable network. IEEE Trans Evol Comput 1: 179–188

    Article  Google Scholar 

  • Elbaum R, Sidi M (1996) Topological design of local-area networks using genetic algorithm. IEEE ACM Trans Netw 4: 766–778

    Article  Google Scholar 

  • Ersoy C, Panwar S (1993) Topological design of interconnected LAN/MAN networks. IEEE J Select Area Commun 11: 1172–1182

    Article  Google Scholar 

  • Esau LR, Williams KC (1966) On teleprocessing system design. A method for approximating the optimal network. IBM Syst J 5: 142–147

    Article  Google Scholar 

  • Fetterolf PC (1990) Design of data networks with spanning tree bridges. In: Proceedings of IEEE international conference on systems, Man, and cybernatics, pp 298–300

  • Fonseca CM, Fleming PJ (1993) Genetic algorithms for multiobjective optimization: formulation, discussion and generalization. In: Proceedings of the 5th international conference on genetic algorithms, pp 416–423

  • Gen M, Ida K, Kim J (1998) A spanning tree-based genetic algorithm for bicriteria topological network design. In: Proceedings of IEEE international conference on evolutionary computation, pp 164–173

  • Glover F (1989) Tabu search—part I. ORSA J Comput 1(3): 190–206

    MATH  Google Scholar 

  • Glover F, Laguna M (1997) Tabu search. Kluwer, Dordrecht

    MATH  Google Scholar 

  • Goldberg DE (1989) Genetic algorithms in search, optimization, and machine learning. Addison-Wesley, Reading

    MATH  Google Scholar 

  • Gupta A, Dally W (2006) Topology optimization of interconnection networks. IEEE Comput Architect Lett 5(1): 10–13

    Article  Google Scholar 

  • Habib S (2005) Redesigning network topology with technology considerations. In: Proceedings of the 9th IFIP/IEEE international symposium on integrated network management, pp 207–219

  • Hamacher H (1978) Ueber logische Verknupfungen Unschalfer Aussagen und deren Zugehoerige Bewertungs-funktione. Progr Cybern Syst Res 3: 276–288

    Google Scholar 

  • Harmatos J, Szentes A, Godor I (2000) Planning of tree-topology UMTS terrestrial access networks. In: Proceedings of the 11th IEEE international symposium on personal, indoor and mobile radio communications, pp 353–357

  • Jeon Y, Kim JC, Kim JO, Shin J, Lee K (2002) An efficient simulated annealing algorithm for network reconfiguration in large-scale distribution systems. IEEE Trans Power Deliv 517(4): 1070–1078

    Article  Google Scholar 

  • Jingpeng L, Kwan R (2001) A fuzzy simulated evolution algorithm for the driver scheduling problem. In: Proceedings of the IEEE congress on evolutionary computation, pp 1115–1122

  • Jingpeng L, Kwan R (2002) A fuzzy evolutionary approach with Taguchi parameter setting for the set covering problem. In: Proceedings of the IEEE congress on evolutionary computation, pp 1203–1208

  • Keiser GE (1989) Local area networks. McGraw-Hill, New York

    Google Scholar 

  • Kennedy J, Eberhart RC (1995) Particle swarm optimization. In: Proceedings of IEEE international conference on neural networks, pp 1942–1948

  • Khan SA, Engelbrecht AP (2007) A new fuzzy operator and its application to topology design of distributed local area networks. Inf Sci 177: 2692–2711

    Article  MATH  Google Scholar 

  • Kirkpatrick S, Gelatt C, Vecchi M (1983) Optimization by simulated annealing. Science 498–516

  • Kling R, Banerjee P (1989) ESP: placement by simulated evolution. IEEE Trans Comput Aided Des 8(3): 245–255

    Article  Google Scholar 

  • Kling R, Banerjee P (1991) Empirical and theoretical studies of the simulated evolution method applied to standard cell placement. IEEE Trans Comput Aided Des 10(10): 1303–1315

    Article  Google Scholar 

  • Laarhoven P, Aarts E (1985) Statistical cooling: a general approach to combinatorial optimization problems. Phillips J Res 40(4): 193–226

    Google Scholar 

  • Laarhoven P, Aarts E (1987) Simulated annealing: theory and applications. Kluwer, Norwell

    MATH  Google Scholar 

  • Li H, Yen V (1997) Fuzzy sets and fuzzy decision-making. Kluwer, Dordrecht

    Google Scholar 

  • Matsuba I (1989) Optimal simulated annealing method and its application to combinatorial problems. In: Proceedings of the international joint conference on neural networks, pp 541–546

  • Miettinen K (2001) Some methods for nonlinear multi-objective optimization. In: Proceedings of the 1st international conference on evolutionary multi-criterion optimization, LNCS, pp 1–20

  • Miyoshi T, Shimizu S, Tanaka Y (2002) Fast topological design with simulated annealing for multicast networks. In: Proceedings of 7th international symposium on computers and communications, pp 959–966

  • Murata T, Oshida H, Gen M (2000) Rule-based weight definition for multiobjective fuzzy scheduling with the OWA operator. In: Proceedings of 26th annual conference of the industrial electronics society, pp 2756–2761

  • Nahar S, Sahni S, Shragowitz E (1985) Experiments with simulated annealing. In: Proceedings of 22nd design automation conference, pp 748–752

  • Perttunen C (1991) Nonparametric cooling schedules in simulated annealing using the normal score transformations. In: Proceedings of the IEEE international conference on systems, man, and cybernetics, pp 609–612

  • Pierre S, Legault G (1998) A genetic algorithm for designing distributed computer network topologies. IEEE Trans Syst Man Cybern 28(2): 249–258

    Article  Google Scholar 

  • Saab Y, Rao V (1990) Stochastic evolution: a fast effective heuristic for some generic layout problems. In: Proceedgins of 27th ACM/IEEE design automation conference, pp 26–31

  • Saab Y, Rao V (1991) Combinatorial optimization by stochastic evolution. IEEE Trans Comput Aided Des 10(4): 525–535

    Article  Google Scholar 

  • Sait S, Ali M, Zaidi A (2005a) Multiobjective VLSI cell placement using distributed simulated evolution algorithm. In: Proceedings of IEEE international symposium on circuits and systems, pp 6226–6229

  • Sait S, Faheemuddin M, Minhas M, Sanaullah S (2005b) Multiobjective VLSI cell placement using distributed genetic algorithm. In: Proceedings of genetic and evolutionary computation conference, pp 1585–1586

  • Sait S, Youssef H (1999) Iterative computer algorithms and their application to engineering. IEEE Computer Science Press

  • Soni S, Narasimhan S, LeBlanc L (2004) Telecommunication access network design with reliability constraints. IEEE Trans Reliab 53(4): 532–541

    Article  Google Scholar 

  • Sportack MA (1999) IP routing fundamentals. Cisco Press, New York

    Google Scholar 

  • Thompson D, Bilbro G (2000) Comparison of a genetic algorithm with a simulated annealing algorithm for the design of an ATM network. IEEE Commun Lett 4(8): 267–269

    Article  Google Scholar 

  • Torra V (1996) Weighted OWA operators for synthesis of information. In: Proceedings of the 5th IEEE international conference on fuzzy systems, pp 966–971

  • Wright J, Loosemore H (2001) An infeasibility objective for use in constrained Pareto optimization. In: Proceedings of the 1st international conference on evolutionary multi-criterion optimization, LNCS, pp 256–268

  • Yager R (1977) Multiple objective decision-making using fuzzy sets. Int J Man Machine Stud 9: 375–382

    Article  MATH  Google Scholar 

  • Yager R (1992) Second order structures in multi-criteria decision making. Int J Man Machine Stud 36: 553–570

    Article  Google Scholar 

  • Yager R (1988) On ordered weighted averaging aggregation operators in multicriteria decisionmaking. IEEE Trans Syst Man Cybern 18(1): 183–190

    Article  MATH  MathSciNet  Google Scholar 

  • Yin-Tsung H, Jer-Sho H (1997) Simulated evolution based code generation for programmable DSP processors. In: Proceedings of IEEE circuits and systems symposium, pp 2593–2596

  • Youssef H, Sait S, Khan SA (2002) Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm. Eng Appl Artif Intell 15: 327–340

    Article  Google Scholar 

  • Zadeh LA (1963) Optimality and non-scalar-valued performance criteria. IEEE Trans Autom Control 8: 59–60

    Article  Google Scholar 

  • Zadeh LA (1965) Fuzzy sets. Inf Contr 8: 338–353

    Article  MATH  MathSciNet  Google Scholar 

  • Zadeh LA (1973) Outline of a new approach to the analysis of complex systems and decision processes. IEEE Trans Syst Man Cybern 3(1): 28–44

    MATH  MathSciNet  Google Scholar 

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  1. Department of Computer Science, University of Pretoria, Pretoria, 0002, South Africa

    Salman A. Khan & Andries P. Engelbrecht

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  1. Salman A. Khan
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  2. Andries P. Engelbrecht
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Correspondence to Salman A. Khan.

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Khan, S.A., Engelbrecht, A.P. Fuzzy hybrid simulated annealing algorithms for topology design of switched local area networks. Soft Comput 13, 45–61 (2009). https://doi.org/10.1007/s00500-008-0292-1

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