Proposal of Two Measures of Complexity Based on Lempel-Ziv for Dynamic Systems: An Application for Manufacturing Systems

Alfaro, Miguel; Vargas, Manuel; Fuertes, Guillermo; Sepúlveda-Rojas, Juan Pedro

doi:10.1155/2018/8692146

Cited by 7 publications

(3 citation statements)

References 34 publications

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“…Alfaro et al [38,39] researched dynamic systems to find new heuristic techniques that generated better solutions or improved the convergence speed.…”

Section: Introductionmentioning

confidence: 99%

Chaotic Honeybees Optimization Algorithms Approach for Traveling Salesperson Problem

et al. 2022

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Due to the difficulty in solving combinatorial optimization problems, it is necessary to improve the performance of the algorithms by improving techniques to deal with complex optimizations. This research addresses the metaheuristics of marriage in honey-bees optimization (MBO) based on the behavior of bees. The current study proposes a technique for solving combinatorial optimization problems within proper computation times. The purpose of this study focuses on the travelling salesperson problem and the application of chaotic methods in important sections of the MBO metaheuristic. Three experiments were conducted to measure the efficiency and quality of the solutions: (1) MBO with chaos to generate initial solutions (MBO2); (2) MBO with chaos in the workers (MBO3); and (3) MBO with chaos to generate initial solutions and the workers (MBO4). The application of chaotic functions in MBO was significantly better at solving the travelling salesperson problem.

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“…Alfaro et al [38,39] researched dynamic systems to find new heuristic techniques that generated better solutions or improved the convergence speed.…”

Section: Introductionmentioning

confidence: 99%

Chaotic Honeybees Optimization Algorithms Approach for Traveling Salesperson Problem

et al. 2022

Self Cite

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“…These are classical methods such as mixed integer linear programming [17,18], nonlinear dynamic programming [19,20], and metaheuristic approaches such as tabu search [21], particle swarm optimization [22], bacterial foraging [23], simulated annealing [24], bee colony [25], and genetic algorithms (GA) [26,27]. Others authors [28] studied the effects of the indicators of complexity of industrial structures. In [26] the authors solved a similar problem, but their study was mainly focused on the comparison between two separation techniques rather than solving the problem directly.…”

Section: Introductionmentioning

confidence: 99%

Optimization of large electric power distribution using a parallel genetic algorithm with dandelion strategy

Sabattin¹,

Fuertes²,

Alfaro³

et al. 2018

Turk J Elec Eng & Comp Sci

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The study of electrical distribution of primary networks design is oriented to reduce the construction costs and the energy losses by transmission. The topology for the implementation of distribution networks may vary according to the geographical characteristics of the final users and requires specialized optimization solutions with metaheuristics to improve the energy performance of the electrical power systems. A parallel genetic algorithm (PGA) is proposed to optimize a tree-based topology for large-scale electric power distribution networks. The proposed PGA uses the dandelion code, which allows obtaining tree-feasible solutions within each iteration of the PGA. This cannot be achieved with other metaheuristic approaches directly. Eight cores are used simultaneously. We achieve a 22.05% improvement when compared to the tree-feasible solutions obtained with its sequential version. Moreover, the computational time required by the PGA is on average 23 times lower than the sequential version. Finally, we find feasible solutions for instances of the problem with up to 50,000 nodes.

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“…For the chaotic time series, the forecast models will have an exponential divergence between the true values and the predicted ones. According to [7,8], the predictability time (T P ) of a system for a disturbance (ε) with an error (Δ) and with the maximum Lyapunov exponent (λ max ) is given by…”

Section: Introductionmentioning

confidence: 99%

Forecast of Chaotic Series in a Horizon Superior to the Inverse of the Maximum Lyapunov Exponent

et al. 2018

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In this article, two models of the forecast of time series obtained from the chaotic dynamic systems are presented: the Lorenz system, the manufacture system, and the volume of the Great Salt Lake of Utah. The theory of the nonlinear dynamic systems indicates the capacity of making good-quality predictions of series coming from dynamic systems with chaotic behavior up to a temporal horizon determined by the inverse of the major Lyapunov exponent. The analysis of the Fourier power spectrum and the calculation of the maximum Lyapunov exponent allow confirming the origin of the series from a chaotic dynamic system. The delay time and the global dimension are employed as parameters in the models of forecast of artificial neuronal networks (ANN) and support vector machine (SVM). This research demonstrates how forecast models built with ANN and SVM have the capacity of making forecasts of good quality, in a superior temporal horizon at the determined interval by the inverse of the maximum Lyapunov exponent or theoretical forecast frontier before deteriorating exponentially.

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Proposal of Two Measures of Complexity Based on Lempel-Ziv for Dynamic Systems: An Application for Manufacturing Systems

Cited by 7 publications

References 34 publications

Chaotic Honeybees Optimization Algorithms Approach for Traveling Salesperson Problem

Chaotic Honeybees Optimization Algorithms Approach for Traveling Salesperson Problem

Optimization of large electric power distribution using a parallel genetic algorithm with dandelion strategy

Forecast of Chaotic Series in a Horizon Superior to the Inverse of the Maximum Lyapunov Exponent

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