Solving multi-objective portfolio optimization problem using invasive weed optimization
Tài liệu tham khảo
Markowitz, 1952, Portfolio selection*, J. Financ., 7, 77
F. Xu, W. Chen, L. Yang. Improved particle swarm optimization for realistic portfolio selection, In: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, SNPD, IEEE, 2007.
Markowitz, 1956, The optimization of a quadratic function subject to linear constraints, Nav. Res. Logist. Q., 3, 111, 10.1002/nav.3800030110
H. Markowitz, Portfolio Selection: Efficient Diversification of Investments, New York, 1959.
Yoshimoto, 1996, The mean-variance approach to portfolio optimization subject to transaction costs, J. Oper. Res. Soc. Jpn., 39, 99, 10.15807/jorsj.39.99
Konno, 1995, A mean-variance-skewness portfolio optimization model, J. Oper. Res. Soc. Jpn., 38, 173, 10.15807/jorsj.38.173
Chang, 2000, Heuristics for cardinality constrained portfolio optimisation, Comput. Oper. Res., 27, 1271, 10.1016/S0305-0548(99)00074-X
Soleimani, 2009, Markowitz-based portfolio selection with minimum transaction lots, cardinality constraints and regarding sector capitalization using genetic algorithm, Expert. Syst. Appl., 36, 5058, 10.1016/j.eswa.2008.06.007
Oh, 2006, Portfolio algorithm based on portfolio beta using genetic algorithm, Expert. Syst. Appl., 30, 527, 10.1016/j.eswa.2005.10.010
Golmakani, 2011, Constrained portfolio selection using particle swarm optimization, Expert. Syst. Appl., 38, 8327, 10.1016/j.eswa.2011.01.020
Zadeh, 1965, Fuzzy sets, Inf. Control., 8, 338, 10.1016/S0019-9958(65)90241-X
Negoita, 1978, Fuzzy sets as a basis for a theory of possibility, Fuzzy Sets Syst., 1, 3, 10.1016/0165-0114(78)90029-5
H. Katagiri, H. Ishii, Fuzzy portfolio selection problem. In: IEEE SMC׳99 Conference Proceedings, International Conference on Systems, Man, and Cybernetics, IEEE, 1999.
Soyster, 1973, Technical note—convex programming with set-inclusive constraints and applications to inexact linear programming, Oper. Res., 21, 1154, 10.1287/opre.21.5.1154
Goldfarb, 2003, Robust portfolio selection problems, Math. Oper. Res., 28, 1, 10.1287/moor.28.1.1.14260
Sadjadi, 2012, Robust optimization framework for cardinality constrained portfolio problem, Appl. Soft Comput., 12, 91, 10.1016/j.asoc.2011.09.006
Ghahtarani, 2013, Robust goal programming for multi-objective portfolio selection problem, Econ. Model., 33, 588, 10.1016/j.econmod.2013.05.006
Cura, 2009, Particle swarm optimization approach to portfolio optimization, Nonlinear Anal.: Real. World Appl., 10, 2396, 10.1016/j.nonrwa.2008.04.023
Deng, 2012, Markowitz-based portfolio selection with cardinality constraints using improved particle swarm optimization, Expert. Syst. Appl., 39, 4558, 10.1016/j.eswa.2011.09.129
J. Kennedy, R. Eberhart, Particle swarm optimization, In: Proceedings of the IEEE International Conference on Neural Networks, 1995, pp. 1942–1948.
J. Kennedy, R.C. Eberhart. A discrete binary version of the particle swarm algorithm, In: 1997 IEEE International Conference on Systems, Man, and Cybernetics, Computational Cybernetics and Simulation, IEEE, 1997.
Y. Shi, R. Eberhart, A modified particle swarm optimizer. In: 1998 IEEE International Conference on Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence, IEEE, 1998.
Y. Shi, R.C. Eberhart, Parameter selection in particle swarm optimization, In: Evolutionary Programming VII, Springer, 1998.
C.A. Coello Coello, M.S. Lechuga. MOPSO: A proposal for multiple objective particle swarm optimization, In: CEC׳02. Proceedings of the 2002 Congress on Evolutionary Computation, IEEE, 2002.
X. Hu, R. Eberhart, Multiobjective optimization using dynamic neighborhood particle swarm optimization, In: Proceedings of the World on Congress on Computational Intelligence, IEEE, 2002.
Clerc, 2002, The particle swarm-explosion, stability, and convergence in a multidimensional complex space, IEEE Trans. Evolut. Comput., 6, 58, 10.1109/4235.985692
W. Chen, et al., Particle swarm optimization for constrained portfolio selection problems, In: 2006 International Conference on Machine Learning and Cybernetics, IEEE, 2006.
Tripathi, 2007, Multi-objective particle swarm optimization with time variant inertia and acceleration coefficients, Inf. Sci., 177, 5033, 10.1016/j.ins.2007.06.018
Niu, 2009, 776
Chen, 2010, The admissible portfolio selection problem with transaction costs and an improved PSO algorithm, Phys. A: Stat. Mech. Appl., 389, 2070, 10.1016/j.physa.2010.01.016
Chang, 2011, Using investment satisfaction capability index based particle swarm optimization to construct a stock portfolio, Inf. Sci., 181, 2989, 10.1016/j.ins.2010.05.008
Tafazzoli, 2011, A new IPSO-SA approach for cardinality constrained portfolio optimization, Int. J. Ind. Eng. Comput., 2, 249
Zhu, 2011, Particle Swarm Optimization (PSO) for the constrained portfolio optimization problem, Expert. Syst. Appl., 38, 10161, 10.1016/j.eswa.2011.02.075
Corazza, 2013, Particle Swarm Optimization with non-smooth penalty reformulation, for a complex portfolio selection problem, Appl. Math. Comput., 224, 611, 10.1016/j.amc.2013.07.091
M. Yuanbin, et al., Based on the Improved Particle Swarm for Portfolio Optimization Study, 2015
Yin, 2015, 164
Mehrabian, 2006, A novel numerical optimization algorithm inspired from weed colonization, Ecol. Inform., 1, 355, 10.1016/j.ecoinf.2006.07.003
Kundu, 2011, Multi-objective optimization with artificial weed colonies, Inf. Sci., 181, 2441, 10.1016/j.ins.2010.09.026
Zdunek, 2010, 698
Pahlavani, 2012, Using a modified invasive weed optimization algorithm for a personalized urban multi-criteria path optimization problem, Int. J. Appl. Earth Obs. Geoinf., 18, 313, 10.1016/j.jag.2012.03.004
Nikoofard, 2012, Multiobjective invasive weed optimization: application to analysis of Pareto improvement models in electricity markets, Appl. Soft Comput., 12, 100, 10.1016/j.asoc.2011.09.005
Pourjafari, 2012, Solving nonlinear equations systems with a new approach based on invasive weed optimization algorithm and clustering, Swarm Evolut. Comput., 4, 33, 10.1016/j.swevo.2011.12.001
Ghasemi, 2014, Solving non-linear, non-smooth and non-convex optimal power flow problems using chaotic invasive weed optimization algorithms based on chaos, Energy, 73, 340, 10.1016/j.energy.2014.06.026
Zhou, 2014, Invasive weed optimization algorithm for optimization no-idle flow shop scheduling problem, Neurocomputing, 137, 285, 10.1016/j.neucom.2013.05.063
P. Wolfe, The reduced-gradient method. Unpublished manuscript, 1962.
Abadie, 1969, Generalization of the Wolfe reduced gradient method to the case of nonlinear constraints, Optimization, 37, 47
Awasthi, 2011, A multi-criteria decision making approach for location planning for urban distribution centers under uncertainty, Math. Comput. Model., 53, 98, 10.1016/j.mcm.2010.07.023
Wang, 2006, On the normalization of interval and fuzzy weights, Fuzzy Sets Syst., 157, 2456, 10.1016/j.fss.2006.06.008
Leung, 2000, Multiobjective programming using uniform design and genetic algorithm, IEEE Trans. Syst. Man Cybern Part C: Appl. Rev., 30, 293, 10.1109/5326.885111
Solimanpur, 2004, A multi-objective genetic algorithm approach to the design of cellular manufacturing systems, Int. J. Prod. Res., 42, 1419, 10.1080/00207540310001638073
Poli, 2007, Particle swarm optimization, Swarm Intell., 1, 33, 10.1007/s11721-007-0002-0
Chen, 2011, A Study of an Improved PSO Algorithm Used in an Adaptive Optics System, J. AICIT, 5, 135
García-Nieto, 2011, Restart particle swarm optimization with velocity modulation: a scalability test, Soft Comput., 15, 2221, 10.1007/s00500-010-0648-1
Yang, 1997
Charnes, 1978, Measuring the efficiency of decision making units, Eur. J. Oper. Res., 2, 429, 10.1016/0377-2217(78)90138-8
Banker, 1984, Some models for estimating technical and scale inefficiencies in data envelopment analysis, Manag. Sci., 30, 1078, 10.1287/mnsc.30.9.1078
Charnes, 1985, Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions, J. Econom., 30, 91, 10.1016/0304-4076(85)90133-2