Multi-Objective Particle Swarm Optimization with time variant inertia and acceleration coefficients

Bandyopadhyay, 2004, Multi-objective GAs quantitative indices and pattern classification, IEEE Transaction on Systems Man and Cybernetics – Part B: Cybernetics, 34, 2088, 10.1109/TSMCB.2004.834438

A. Carlisle, G. Dozier, Adapting particle swarm optimization to dynamic environments, in: Proceedings of International Conference on Artificial Intelligence (ICAI 2000), Las Vegas, Nevada, USA, 2000, pp. 429–434.

A. Carlisle, G. Dozier, Tracking changing extrema with adaptive particle swarm optimizer, in: Proceedings of the 5th Biannual World Automation Congress, Orlando, Florida, USA, 2002, pp. 265–270.

Clerc, 2002, The particle swarm: explosion stability and convergence in a multi-dimensional complex space, IEEE Transactions on Evolutionary Computation, 6, 58, 10.1109/4235.985692

Coello, 2002, MOPSO: A proposal for multiple objective particle swarm optimization, 1051

Coello, 2004, Handling multiple objectives with particle swarm optimization, IEEE Transactions on Evolutionary Computation, 8, 256, 10.1109/TEVC.2004.826067

Coello, 2001

Corne, 2001, PESA-II: region-based selection in evolutionary multiobjective optimization, 283

Deb, 2001

Deb, 2002, A fast and elitist multi-objective genetic algorithm: NSGA-II, IEEE Transactions On Evolutionary Computation, 6, 182, 10.1109/4235.996017

K. Deb, L. Thiele, M. Laumanns, E. Zitzler, Scalable Test Problems for Evolutionary Multi-Objective Optimization. Technical Report TIK-Technical Report No. 112, Institut fur Technische Informatik und Kommunikationsnetze, ETH Zurich Gloriastrasse 35., ETH-Zentrum, CH-8092, Zurich, Switzerland, July 2001.

Engelbrecht, 2006

S.C. Esquivel, C.A.C. Coello, On the use of particle swarm optimization with multimodal functions, in: The 2003 Congress on Evolutionary Computation, 2003. CEC ’03, vol. 2, 2003, pp. 1130– 1136.

J.E. Fieldsend, S.Singh, A multi-objective algorithm based upon particle swarm optimization, an efficient data structure and turbulence, in: Proceedings of UK Workshop on Computational Intelligence (UKCI’02), vol. 2–4, Bermingham, UK, September 2002, pp. 37–44.

Hu, 2002, Multiobjective Optimization Using Dynamic Neighbourhood Particle Swarm Optimization

J. Kennedy, R. Eberhart, Particle swarm optimization, in: IEEE International Conference Neural Networks, 1995, pp. 1942–1948.

Knowles, 2000, Approximating the nondominated front using the Pareto archived evolution strategy, Evolutionary Computation, 8, 149, 10.1162/106365600568167

Li, 2003, A non-dominated sorting particle swarm optimizer for multi-objective optimization, vol. 2723, 37

Michalewicz, 1992

Monson, 2006, Adaptive diversity in PSO, 59

Montiel, 2006, Human evolutionary model: a new approach to optimization, Information Sciences, 177, 2075

Mostaghim, 2003

Pal, 1998, Genetic algorithms for generation of class boundaries, IEEE Transaction on Systems Man and Cybernetics – Part B: Cybernetics, 28, 816, 10.1109/3477.735391

K.E. Parsopoulos, M.N. Vrahatis, Particle swarm optimization method in multiobjective problems, in: Proceedings of the 2002 ACM Symposium on Applied Computing (SAC 2002), 2002, pp. 603–607.

Penev, 2005, Free search – a comparative analysis, Information Sciences, 172, 173, 10.1016/j.ins.2004.09.001

Ratnaweera, 2004, Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients, IEEE Transactions On Evolutionary Computation, 8, 240, 10.1109/TEVC.2004.826071

J.D. Schaffer, Some experiments in machine learning using vector evaluated genetic algorithm, Ph.D. Thesis, Vanderbilt University, Nashville,TN, 1984.

Y. Shi, R.C. Eberhart, A modified particle swarm optimizer, in: IEEE Conference on Evolutionary Computation, 1998, pp. 69–73.

Y. Shi, R.C. Eberhart, Parameter selection in particle swarm optimization. in: Evolutionary Programming VII: Proceedings of the Seventh Annual Conference on Evolutionary Programming, New York, 1998, pp. 591–600.

Y. Shi, R.C. Eberhart, Empirical study of particle swarm optimization, in: IEEE International Congress on Evolutionary Computation, vol. 3, 1999, pp. 101–106.

F. van den Bergh. An analysis of particle swarm optimizers, Ph.D. Thesis, Faculty of Natural and Agricultural Science, University of Pretoria, Pretoria, November 2001.

van den Bergh, 2006, A study of particle swarm optimization particle trajectories, Information Sciences, 176, 937, 10.1016/j.ins.2005.02.003

D.V. Veldhuizen, Multiobjective evolutionary algorithms: classifications, analysis and new innovations, Ph.D. Thesis, Department of Electrical and Computer Engineering, Air Force Institute of Technology (1999), Dayton, 1999.

T. Ying, Y.P. Yang, J.C. Zeng. An enhanced hybrid quadratic particle swarm optimization, in: Sixth International Conference on Intelligent Systems Design and Applications, 2006, ISDA ’06, vol. 2, October 2006, pp. 980–985.

Zadeh, 2005, Towards a generalized theory of uncertainity (GTU) – an outline, Information Sciences, 172, 1, 10.1016/j.ins.2005.01.017

Y. Zhang, S. Huang. A novel multi-objective particle swarm optimization for buoys-arrangement design, in: Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT 2004), 2004, pp. 24–30.

E. Zitzler, M. Laumanns, L. Thiele, SPEA2: Improving the strength Pareto evolutionary algorithm. technical report TIK-103, Computer Engineering and Network Laboratory (TIK), Swiss Fedral Institute of Technology (ETH), Gloriastrasse 35, CH-8092 Zurich, Swidzerland, May 2001.