A new hybrid genetic algorithm for global optimization

Sotiropoulos, D. G.; Stavropoulos, C. E.; Vrahatis, N.

doi:10.1016/s0362-546x(96)00367-7

Cited by 33 publications

(22 citation statements)

References 8 publications

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“…In the area of optimization, various methods (deterministic and stochastic) have been developed to solve global optimization problems (Floudasa, Akrotirianakisa, Caratzoulasa, Meyera, & Kallrathb, 2005;Horst & Tuy, 1996;Kennedy & Eberhart, 1995;Schaffler, 2012;Shi & Eberhart, 1999;Sotiropoulos, Stavropoulos, & Vrahatis, 1997;Torn & Zilinskas, 1989). Depending on context, each approach has its own particular advantages and disadvantages.…”

Section: Controller Design Methodsmentioning

confidence: 99%

A measurement-based technique for designing fixed-order RST controllers and application to a coupled water tank system

Khadraoui

Nounou

et al. 2014

Systems Science & Control Engineering

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This paper addresses the control design problem for unknown linear single-input single-output systems using a set of measurements. In standard control methods, controllers are designed on the basis of a mathematical model. Such a mathematical model, which describes the behavior of the system, can be developed using either physical laws or measured data. However, due to the complex dynamics of many physical systems, some prior assumptions are usually made to build simplified models. The efficacy of such model-based control techniques depends greatly on the quality of models used. Hence, data-based control design methods appeared as an alternative to model-based methods. Such data-based techniques are powerful in the sense that no mathematical model is needed for controller design. In this paper, we propose an approach that uses frequency response data to directly design controllers without going through any modeling stage. The main idea of our proposed method is to design polynomial RST controllers, for which the closed-loop frequency response fits a desired frequency response that describes some desired performance specifications. This problem is formulated as an error minimization problem, which can be solved using efficient optimization algorithms. The main feature of our proposed control approach is that it enables the designer to pre-select the controller structure, which allows the design of low-order controllers. Moreover, this control design approach does not depend on the increasing order and complexity of the system. An application to water level control of a coupled tank system is presented to validate and illustrate the efficacy of the proposed approach.

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Section: Controller Design Methodsmentioning

confidence: 99%

A measurement-based technique for designing fixed-order RST controllers and application to a coupled water tank system

Khadraoui

Nounou

et al. 2014

Systems Science & Control Engineering

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“…Integrative methods embed one algorithm within the other. Sotiropoulos et al [2] used an Interval Branch and Bound (IB&B) to reduce the domain to a list of �-large subspaces. A Genetic Algorithm (GA) [3] was then initialized within each subspace to improve the upper bound of the global minimum.…”

Section: Motivationmentioning

confidence: 99%

Preventing Premature Convergence and Proving the Optimality in Evolutionary Algorithms

Vanaret

Gotteland²,

Durand³

et al. 2014

Lecture Notes in Computer Science

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“…Sotiropoulos et al [16] use an interval branch and bound technique to create subregions and choose the midpoint of each subregion to be individuals in an initial population for GA.…”

Section: The Modificationsmentioning

confidence: 99%

Combining Interval Branch and Bound and Stochastic Search

Bunnag

2014

Abstract and Applied Analysis

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This paper presents global optimization algorithms that incorporate the idea of an interval branch and bound and the stochastic search algorithms. Two algorithms for unconstrained problems are proposed, the hybrid interval simulated annealing and the combined interval branch and bound and genetic algorithm. The numerical experiment shows better results compared to Hansen's algorithm and simulated annealing in terms of the storage, speed, and number of function evaluations. The convergence proof is described. Moreover, the idea of both algorithms suggests a structure for an integrated interval branch and bound and genetic algorithm for constrained problems in which the algorithm is described and tested. The aim is to capture one of the solutions with higher accuracy and lower cost. The results show better quality of the solutions with less number of function evaluations compared with the traditional GA.

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A new hybrid genetic algorithm for global optimization

Cited by 33 publications

References 8 publications

A measurement-based technique for designing fixed-order RST controllers and application to a coupled water tank system

A measurement-based technique for designing fixed-order RST controllers and application to a coupled water tank system

Preventing Premature Convergence and Proving the Optimality in Evolutionary Algorithms

Combining Interval Branch and Bound and Stochastic Search

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