| Title |
Experimental analysis of hybrid genetic algorithm for the grey pattern quadratic assignment problem / |
| Authors |
Stanevičienė, Evelina ; Misevičius, Alfonsas ; Ostreika, Armantas |
| DOI |
10.5755/j01.itc.48.2.23114 |
| Full Text |
|
| Is Part of |
Information technology and control = Informacinės technologijos ir valdymas.. Kaunas : KTU. 2019, vol. 48, iss. 2, p. 335-356.. ISSN 1392-124X. eISSN 2335-884X |
| Keywords [eng] |
computational intelligence, heuristics, hybrid genetic algorithms ; combinatorial optimization ; grey pattern quadratic assignment problem ; component-based analysis |
| Abstract [eng] |
In this paper, we present the results of the extensive computational experiments with the hybrid genetic algorithm (HGA) for solving the grey pattern quadratic assignment problem (GP-QAP). The experiments are on the basis of the component-based methodology where the important algorithmic ingredients (features) of HGA are chosen and carefully examined. The following components were investigated: initial population, selection of parents, crossover procedures, number of offspring per generation, local improvement, replacement of population, population restart). The obtained results of the conducted experiments demonstrate how the methodical redesign (reconfiguration) of particular components improves the overall performance of the hybrid genetic algorithm. |
| Published |
Kaunas : KTU |
| Type |
Journal article |
| Language |
English |
| Publication date |
2019 |
| CC license |
|
