Genetic algorithms and Machine Learning

@article{Goldberg2004GeneticAA,
  title={Genetic algorithms and Machine Learning},
  author={David E. Goldberg},
  journal={Machine Learning},
  year={2004},
  volume={3},
  pages={95-99}
}
  • D. Goldberg
  • Published 2004
  • Computer Science
  • Machine Learning
There is no a priori reason why machine learning must borrow from nature. A field could exist, complete with well-defined algorithms, data structures, and theories of learning, without once referring to organisms, cognitive or genetic structures, and psychological or evolutionary theories. Yet at the end of the day, with the position papers written, the computers plugged in, and the programs debugged, a learning edifice devoid of natural metaphor would lack something. It would ignore the fact… 
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11 Citations
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11 Citations

Why Simheuristics? Benefits, Limitations, and Best Practices When Combining Metaheuristics with Simulation

This paper argues that approaches combining simulation with meta heuristics not only constitute a natural extension of metaheuristics, but also should be considered as a “first resort” method when dealing with large-scale stochastic optimization problems, which constitute most realistic problems in industry and business.

A Method for Parameters Estimation in a Dynamical Model of Ebola Virus Transmission in Sierra Leone

The experimental results indicate that the GA has strong competitiveness compared with the classical method, and it is a feasible method for estimating the parameters of infectious disease models.

A Hybrid SSA and SMA with Mutation Opposition-Based Learning for Constrained Engineering Problems

Considering the characteristics and advantages of both the above optimization algorithms, SMA is integrated into the leader position updating equations of SSA so that the proposed algorithm can utilize these two algorithms' advantages to enhance global optimization performance.

An Efficient Adaptive Salp Swarm Algorithm Using Type II Fuzzy Entropy for Multilevel Thresholding Image Segmentation

An improved SSA called as adaptive salp swarm algorithm (ASSA) is proposed, along with type II fuzzy entropy, and robustness is tested with the efficiency of the proposed method to multilevel segmentation of image.

Adaptive complex network topology with fitness distance correlation framework for particle swarm optimization

To avoid the particle swarm falling into premature convergence, this study introduces a random drift strategy to make the particles drift slightly and reduces the risk of premature convergence.

Gaussian Perturbation Specular Reflection Learning and Golden-Sine-Mechanism-Based Elephant Herding Optimization for Global Optimization Problems

An improved algorithm to solve elephant herding optimization shortcomings, called Gaussian perturbation specular reflection learning and golden-sine-mechanism-based EHO (SRGS-EHO), is proposed and can be applied to solve the problems encountered in real production.

Dynamic Maintenance Scheduling Based on Cost Analysis and Genetic Algorithm for Offshore Facilities

This paper introduces a dynamic Maintenance Work Order (MWO) schedule model for offshore facilities’ daily maintenance management based on cost analysis and real-time data processed by customized heuristic algorithms.

Quantum Mechanics/Fluctuating Charge Protocol to Compute Solvatochromic Shifts

The reliability and robustness of the QM/FQ approach are demonstrated by challenging the model to simulate solvatochromic shifts of four organic chromophores, which display large shifts when dissolved in apolar, aprotic or polar, protic solvents.

An Optimization Method for the Train Service Network Design Problem

The computational results show that the proposed approach can obtain high-quality solutions with satisfactory speed, and comparative analysis on a case that assumes all the shuttle train services between any two adjacent yards to be provided without optimization reveals some interesting insights.

High fidelity modelling and GA optimized control of yaw dynamics of a custom built remotely operated unmanned underwater vehicle

References

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