A hybrid multi-objective PSO algorithm with local search strategy for VLSI partitioning

Wenzhong Guo1, Genggeng Liu1, Guolong Chen1, Shao-jun Peng1
1College of Mathematics and Computer Science, Fuzhou University, Fuzhou, 350116, China

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Dutt S, Deng W Y. A probability-based approach to VLSI circuit partitioning. In: Proceedings of the 33rd Design Automation Conference. 1996, 100–105

Dutt S. Cluster-aware iterative improvement techniques for partitioning large VLSI circuits. ACM Transactions on Design Automation of Electronic Systems, 2002, 7(1): 91–121

Wei Y C, Cheng C K. Ratio cut partitioning for hierarchical designs. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 1991, 10(7): 911–921

Fiduccia C M, Mattheyses B M. A linear-time heuristic for improving network partitions. In: Proceedings of the 19th Design Automation Conference. 1982, 175–181

Krishnamurthy B. An improved min-cut algorithm for partitioning VLSI networks, IEEE Transactions on Computer. 1984, 100(5): 438–446

Iqbal S M A, Monir M I, Sayeed T. A concurrent approach to clustering algorithm with applications to VLSI domain. In: Proceedings of the 11th International Conference on Computer and Information Technology. 2008, 476–480

Li J H, Behjat L. A connectivity based clustering algorithm with application to VLSI circuit partitioning. IEEE Transactions on Circuits and Systems II: Express Briefs, 2006, 53(5): 384–388

Barnard S T, Simon H D. Fast multilevel implementation of recursive spectral bisection for partitioning unstructured problems. Concurrency: Practice and Experience, 1994, 6(2): 101–117

Lang K J. Fixing two weaknesses of the spectral method. In: Proceedings of the 2005 Neural Infromation Processing Systems. 2005, 715–722

Kolar D, Puksec J D, Branica I. VLSI circuit partition using simulated annealing algorithm. In: Proceedings of the 12th IEEE Mediterranean on Electrotechnical Conference. 2004, 205–208

Sait S M, El-Maleh A H, Al-Abaji R H. General iterative heuristics for VLSI multiobjective partitioning. In: Proceedings of the 2003 IEEE International, Symposium on Circuits and Systems. 2003, 5: V497–V500

Chen Z Q, Wang R L, Okazaki K. An efficient genetic algorithm based approach for the minimum graph bisection problem. International Journal of Computer Science and Network Security, 2008, 8(6): 118–124

Nan G F, Li M Q, Kou J S. Two novel encoding strategies based genetic algorithms for circuit partitioning. In: Proceedings of the 3rd International Conference on Machine Learning and Cybernetics. 2004, 2182–2188

Sait S M, El-Maleh A H, Al-Abaji R H. Evolutionary algorithms for VLSI multi-objective netlist partitioning. Engineering Applications of Artificial Intelligence, 2006, 19(3): 257–268

Kennedy J, Eberhart R C. Particle swarm optimization. In: Proceedings of the IEEE International Conference on Neural Networks. 1995, 1942–1948

Wang Y, Cai Z X. A hybrid multi-swarm particle swarm optimization to solve constrained optimization problems. Frontiers of Computer Science in China, 2009, 3(1): 38–52

Peng S J, Chen G L, Guo W Z. A multi-objective algorithm based on discrete PSO for VLSI partitioning problem. Quantitative Logic and Soft Computing, 2010, 82: 651–660

Chen G L, Guo W Z, Chen Y Z. A PSO-based intelligent decision algorithm for VLSI floorplanning. Soft Computing, 2010, 14(12): 1329–1337

Liu H, Cai ZX, Wang Y. Hybridizing particle swarm optimization with differential evolution for constrained numerical and engineering optimization. Applied Soft Computing, 2010, 10(2): 629–640

Fu Y G, Ding M Y, Zhou C P. Phase Angle-encoded and quantumbehaved particle swarm optimization applied to three-dimensional route planning for UAV. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 2012, 42(2): 511–526

Hung J C. Modified particle swarm optimization structure approach to direction of arrival estimation. Applied Soft Computing, 2013, 13(1): 315–320

Guo W Z, Zhang B, Chen G L, Wang X F, Xiong N. A PSO-optimized minimum spanning tree-based topology control Scheme for wireless sensor networks. International Journal of Distributed Sensor Networks, 2013 (2013): Article 985410

Peng S J, Chen G L, Guo W Z. A discrete PSO for partitioning in VLSI circuit. In: Proceedings of the 2009 International Conference on Computational Intelligence and Software Engineering. 2009, 1–4

Areibi S, Thompson M. A new model for macrocell partitioning. In: Proceedings of the 16th International Conference on Computers and Their Applications. 2001, 161–165

Ababei C, Navaratnasothie S, Bazargan K, Karypis G. Multi-objective circuit partitioning for cut size and path-based delay minimization. In: Proceedings of the International Conference on Computer-Aided Design. 2002, 181–185

Kahng A B, Xu X. Local Unidirectional bias for cutsize-delay tradeoff in performance-driven bipartitioning. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2003, 23(4): 464–471

Kennedy J, Eberhart R C. A discrete binary version of the particle swarm algorithm. In: Proceedings of the 1997 World Multiconference on Systemics, Cybernetics and Informatics. 1997, 4104–4109

Clerc M. Discrete particle swarm optimization, illustrated by the traveling salesman problem. New Optimization Techniques in Engineering, 2004, 141: 219–239

Chen W N, Zhang J, Chung H S H, Zhong W L, Wu W G, Shi Y H. A novel set-based particle swarm optimization method for discrete optimization problems. IEEE Transactions on Evolutionary Computation, 2010, 14(2): 278–300

Qin J, Li X, Yin Y. An algorithmic framework of discrete particle swarm optimization. Applied Soft Computing, 2012, 12(3): 1125–1130

Pan Q K, Tasgetiren M F, Liang Y C. A discrete particle swarm optimization algorithm for the permutation flowshop sequecing problem with makespan criteria. In: Proceedings of the 26th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence. 2006, 19–31

Guo W Z, Xiong N X, Vasilakos A V, Chen G L, Yu C L. Distributed k-connected fault-tolerant topology control algorithms with PSO in future autonomic sensor systems. International Journal of Sensor Networks, 2012, 12(1): 53–62

Balling R. The maximin fitness function: multiobjective city and regional planning. In: Proceedings of the 2nd International Conference on Evolutionary Multi-Criterion Optimization. 2003, 1–15

Laumanns M, Thiele L, Deb K, Zitzler E. Combining convergence and diversity in evolutionary multi-objective optimization. Evolutionary Computation, 2002, 10(3): 263–282

Steuer R E. Multiple Criteria Optimization: Theory, Computation, and Application. New York: John Wiley Sons, 1986

Zitzler E, Laumanns M, and Thiele L. SPEA2: improving the strength pareto evolutionary algorithm. In: K. C. Giannakoglou, D. T. Tsahalis, J. P’eriaux, K. D. Papailiou, T. Fogarty, eds. Evolutionary Methods for Design Optimization and Control with Applications to Industrial Problems, International Center for Numerical Methods in Engineering, 2001, 95–100

Zitzler E. Evolutionary Algorithms for Multiobjective Optimization: Methods and Applications. Zurich: Swiss Federal Institute of Technology, 1999

Zitzler E, Thiele L, Laumanns M, Fonseca C M, Da Fonseca V G. Performance assessment of multiobjective optimizers: an analysis and review. IEEE Transactions on Evolutionary Computation, 2003 (7): 117–132

Conover W J. Practical Nonparametric Statistics. New York: Wiley, 1999