Deriving Smaller Orthogonal Arrays from Bigger Ones with Genetic Algorithm

11/25/2021
by   Luca Mariot, et al.
0

We consider the optimization problem of constructing a binary orthogonal array (OA) starting from a bigger one, by removing a specified amount of lines. In particular, we develop a genetic algorithm (GA) where the underlying chromosomes are constant-weight binary strings that specify the lines to be cancelled from the starting OA. Such chromosomes are then evolved through balanced crossover and mutation operators to preserve the number of ones in them. The fitness function evaluates the matrices obtained from these chromosomes by measuring their distance from satisfying the constraints of an OA smaller than the starting one. We perform a preliminary experimental validation of the proposed genetic algorithm by crafting the initial OA as a random permutation of several blocks of the basic parity-check array, thereby guaranteeing the existence of an optimal solution.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/27/2020

A Genetic Algorithm Based Approach for Satellite Autonomy

Autonomous spacecraft maneuver planning using an evolutionary algorithmi...
research
04/18/2021

A Rank based Adaptive Mutation in Genetic Algorithm

Traditionally Genetic Algorithm has been used for optimization of unimod...
research
03/22/2023

CSRX: A novel Crossover Operator for a Genetic Algorithm applied to the Traveling Salesperson Problem

In this paper, we revisit the application of Genetic Algorithm (GA) to t...
research
10/06/2022

Genetic algorithm formulation and tuning with use of test functions

This work discusses single-objective constrained genetic algorithm with ...
research
08/31/2022

A GPU accelerated Genetic Algorithm for the Construction of Hadamard Matrices

We use a genetic algorithm to construct Hadamard Matrices. The initial p...
research
04/23/2019

Balanced Crossover Operators in Genetic Algorithms

In several combinatorial optimization problems arising in cryptography a...
research
03/08/2020

Real-World Airline Crew Pairing Optimization: Customized Genetic Algorithm versus Column Generation Method

Airline crew cost is the second-largest operating cost component and its...

Please sign up or login with your details

Forgot password? Click here to reset