A hybrid PSO approach for solving non-convex optimization problems

Journal title

Archives of Control Sciences




No 1

Publication authors

Divisions of PAS

Nauki Techniczne


Archives of Control Sciences welcomes for consideration papers on topics of significance in broadly understood control science and related areas, including: basic control theory, optimal control, optimization methods, control of complex systems, mathematical modeling of dynamic and control systems, expert and decision support systems and diverse methods of knowledge modelling and representing uncertainty (by stochastic, set-valued, fuzzy or rough set methods, etc.), robotics and flexible manufacturing systems. Related areas that are covered include information technology, parallel and distributed computations, neural networks and mathematical biomedicine, mathematical economics, applied game theory, financial engineering, business informatics and other similar fields.

Aims and Scope: Archives of Control Sciences publishes papers in the broadly understood field of control science and related areas while promoting the closer integration of the Polish, as well as other Central and East European scientific communities with the international world of science.


Committee of Automatic Control and Robotics PAS




ISSN 1230-2384


Outrata J. (1998), Nonsmooth approach to optimization problems with equilibrium constraints. Nonconvex optimization and its applications. ; Bertsekas D. (1999), Nonlinear programming. ; Chen Y. (1995), The nonlinear bilevel programming problem: Formulations, regularity and optimality conditions, Optimization, 32, 193, ; Holland J. (1992), Control and Artificial Intelligence. ; Koza J. (1992), Genetic programming: On the programming of computers by means of natural selection. ; Kennedy J. (1995), R. Eberhart: Particle swarm optimization, null. ; Phuangpornpitak N. (2010), A study of particle swarm technique for renewable energy power systems, null, 1. ; V.N. Dieu and W. Ongsakul: Economic dispatch with emission and transmission constraints by augmented Lagrange Hopfield network. <i>Trans. in Power System Optimization (GJTO)</i> <a target="_blank" href=''></a> ; Dieu V. (2006), Enhanced merit order and augmented Lagrange Hopfield network for ramp rate constrained unit commitment, null. ; Huang Y. (2007), Improved Lagrange nonlinear programming neural networks for inequality constraints, null. ; Kuhn H. (1951), Nonlinear programming, null, 481. ; Binmore K. (2007), Calculus concepts and methods. ; Sandgren E. (1990), Nonlinear integer and discrete programming in mechanical design optimization, J. of Mechanical Deigns - T. ASME, 112, 2, 223, ; A. Belegundu: A study of mathematical programming methods for structural optimization. PhD thesis, Department of Civil Environmental Engineering, University of Iowa, Iowa, 1982. ; Coello C. (2008), Solving engineering optimization problems with simple constrained particle swarm optimizer, Informatica, 32, 319. ; Shi Y. (1998), A modified particle swarm optimizer, null, 69. ; F. van Den Bergh: An analysis of particle swarm optimizers. PhD thesis, University of Pretoria, 2001. ; Zitzler E. (2004), Metaheuristics for Multiobjective Optimisation, Lecture Notes in Economics and Mathematical Systems. ; Rose H. (2002), Linear algebra. A pure mathematical approach, 57. ; Glover F. (1989), Tabu search, Part I, ORSA J. on Computing, 1, 3, 190, ; Bland J. (1991), Tabu search and design optimization, Computer - aided design, 23, 3, 195, ; Thesen A. (1998), Design and evaluation of tabu search algorithms for Mmultiprocessor scheuling, J. of Hueristics, 4, 141,