Flipping the switch on local exploration: Genetic Algorithms with Reversals

by   Ankit Grover, et al.

One important feature of complex systems are problem domains that have many local minima and substructure. Biological systems manage these local minima by switching between different subsystems depending on their environmental or developmental context. Genetic Algorithms (GA) can mimic this switching property as well as provide a means to overcome problem domain complexity. However, standard GA requires additional operators that will allow for large-scale exploration in a stochastic manner. Gradient-free heuristic search techniques are suitable for providing an optimal solution in the discrete domain to such single objective optimization tasks, particularly compared to gradient based methods which are noticeably slower. To do this, the authors turn to an optimization problem from the flight scheduling domain. The authors compare the performance of such common gradient-free heuristic search algorithms and propose variants of GAs which perform well over our problem and across all benchmarks. The Iterated Chaining (IC) method is also introduced, building upon traditional chaining techniques by triggering multiple local searches instead of the singular action of a mutation operator. The authors will show that the use of multiple local searches can improve performance on local stochastic searches, providing ample opportunity for application to a host of other problem domains.


page 1

page 2

page 3

page 4


The FAIRy Tale of Genetic Algorithms

Genetic Algorithm (GA) is a popular meta-heuristic evolutionary algorith...

Genetic Algorithm: Reviews, Implementations, and Applications

Nowadays genetic algorithm (GA) is greatly used in engineering pedagogy ...

Genetic Random Weight Change Algorithm for the Learning of Multilayer Neural Networks

A new method to improve the performance of Random weight change (RWC) al...

Faster Perturbed Stochastic Gradient Methods for Finding Local Minima

Escaping from saddle points and finding local minima is a central proble...

Selecting Efficient Features via a Hyper-Heuristic Approach

By Emerging huge databases and the need to efficient learning algorithms...

Analyzing Search Topology Without Running Any Search: On the Connection Between Causal Graphs and h+

The ignoring delete lists relaxation is of paramount importance for both...

Decoding Nature with Nature's Tools: Heterotic Line Bundle Models of Particle Physics with Genetic Algorithms and Quantum Annealing

The string theory landscape may include a multitude of ultraviolet embed...

Please sign up or login with your details

Forgot password? Click here to reset