APPLICATION OF GENETIC ALGORITHMS TO SOLVE WAREHOUSE SPACE ALLOCATION PROBLEM

 

Authors
Medrano Pilataxi, Diego Rene
Format
MasterThesis
Status
publishedVersion
Description

In this study the genetic algorithm (GA) has been successfully applied to solve an optimization problem that will contribute to the solution of the warehouse space allocation problem. The potential solution encoded in the genetic sequence of chromosomes depicts the warehouse layout that results in more efficient paths to be followed by automated guided vehicles (AGVs) in order to move materials within the premises. In particular, the present project associates genes with warehouses locations and suggests the optimal gene?s sequence or warehouse?s layout to obtain the shortest path to completing a given sequence of tasks typically occurring in a certain period of time. The performance of GA algorithm depends on the genetic operators (such as selection, crossover and mutation) used. In this project, the performance of GA using different genetic operators including intuitive recombination process for crossover and interchanging genes for mutation, are evaluated.

Publication Year
2015
Language
eng
Topic
GNETIC ALGORITHM
MACHINE LEARNING
GENETIC ALGORITHMS
SPACE ALLOCATION
Repository
Repositorio SENESCYT
Get full text
http://repositorio.educacionsuperior.gob.ec/handle/28000/3760
Rights
openAccess
License