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- Title
IMPROVING INITIAL POPULATION FOR GENETIC ALGORITHM USING THE MULTI LINEAR REGRESSION BASED TECHNIQUE (MLRBT).
- Authors
Alkafaween, Esra'a; Hassanat, Ahmad B. A.; Tarawneh, Sakher
- Abstract
Genetic algorithms (GAs) are powerful heuristic search techniques that are used successfully to solve problems for many different applications. Seeding the initial population is considered as the first step of the GAs. In this work, a new method is proposed, for the initial population seeding called the Multi Linear Regression Based Technique (MLRBT). That method divides a given large scale TSP problem into smaller sub-problems and the technique works frequently until the sub-problem size is very small, four cities or less. Experiments were carried out using the well-known Travelling Salesman Problem (TSP) instances and they showed promising results in improving the GAs' performance to solve the TSP.
- Subjects
GENETIC algorithms; TRAVELING salesman problem; REGRESSION analysis; MULTILINEAR algebra; COMPUTER science
- Publication
Komunikácie, 2021, Vol 23, Issue 1, pE1
- ISSN
1335-4205
- Publication type
Article
- DOI
10.26552/com.C.2021.1.E1-E10