| dc.contributor.author |
Ferentinos, KP |
en |
| dc.contributor.author |
Albright, LD |
en |
| dc.date.accessioned |
2014-06-06T06:46:35Z |
|
| dc.date.available |
2014-06-06T06:46:35Z |
|
| dc.date.issued |
2005 |
en |
| dc.identifier.issn |
09521976 |
en |
| dc.identifier.uri |
http://dx.doi.org/10.1016/j.engappai.2004.11.005 |
en |
| dc.identifier.uri |
http://62.217.125.90/xmlui/handle/123456789/3097 |
|
| dc.subject |
Genetic algorithms |
en |
| dc.subject |
Greenhouse |
en |
| dc.subject |
Lighting system design |
en |
| dc.subject |
Optimal design |
en |
| dc.subject |
Supplemental lighting |
en |
| dc.subject.other |
Automation |
en |
| dc.subject.other |
Greenhouses |
en |
| dc.subject.other |
Investments |
en |
| dc.subject.other |
Lighting |
en |
| dc.subject.other |
Lighting fixtures |
en |
| dc.subject.other |
Optimization |
en |
| dc.subject.other |
Photosynthesis |
en |
| dc.subject.other |
Systems analysis |
en |
| dc.subject.other |
Greenhouse structure |
en |
| dc.subject.other |
Lighting system design |
en |
| dc.subject.other |
Optimal design |
en |
| dc.subject.other |
Supplemental lighting |
en |
| dc.subject.other |
Genetic algorithms |
en |
| dc.subject.other |
Algorithms |
en |
| dc.subject.other |
Automation |
en |
| dc.subject.other |
Greenhouses |
en |
| dc.subject.other |
Illumination |
en |
| dc.subject.other |
Investment |
en |
| dc.subject.other |
Optimization |
en |
| dc.subject.other |
Photosynthesis |
en |
| dc.title |
Optimal design of plant lighting system by genetic algorithms |
en |
| heal.type |
journalArticle |
en |
| heal.identifier.primary |
10.1016/j.engappai.2004.11.005 |
en |
| heal.publicationDate |
2005 |
en |
| heal.abstract |
A genetic algorithm technique is developed for the optimal design of a supplemental lighting system for greenhouse crop production. The approach uses the evolutionary parallel search capabilities of genetic algorithms to design the pattern layout of the lamps (luminaires), their mounting heights and their wattages. The total number and the exact positions of luminaires are not predefined (even though possible positions lay on a fixed grid layout), thus the genetic algorithm system has a large degree of freedom in the designing process. The possibilities of mounting heights and luminaire wattages are limited to four different values for each luminaire in this study. A fitness function for the genetic algorithm was developed, taking into account light uniformity, light intensity capability, shading effects of the design, as well as operational and investment costs. The systems designed by the genetic algorithm show improved values of light uniformity and substantial savings without any effect on the light capacity capabilities of the system. Innovative automatically designed systems compare favorably with typical and expert-designed lighting systems. © 2004 Elsevier Ltd. All rights reserved. |
en |
| heal.journalName |
Engineering Applications of Artificial Intelligence |
en |
| dc.identifier.issue |
4 |
en |
| dc.identifier.volume |
18 |
en |
| dc.identifier.doi |
10.1016/j.engappai.2004.11.005 |
en |
| dc.identifier.spage |
473 |
en |
| dc.identifier.epage |
484 |
en |