Abstrakt
Bioethanol is a liquid fuel for which a significant increase in the share of energy sources has been observed in the economies of many countries. The most significant factor in popularizing bioethanol is the profitability of investments in construction of facilities producing this energy source, as well as the profitability of its supply chain. With the market filled with a large amount of equipment used in the bioethanol production process, it is often difficult to make an optimal decision regarding the investment. Another issue is the location of the plant itself. Economic benefits are strongly associated with costs of equipment and materials, the amount of revenue from sales, and transportation costs. This article presents an attempt to solve this problem by using several swarm algorithms – new and fast-growing optimisation techniques. By employing ant colony optimization, river formation dynamics, particle swarm optimization, and cuckoo search algorithms in the task of bioethanol plant investment planning, the overall suitability of this type of technique has been tested. Moreover, the results allow us to determine which of the preceding algorithms is the most efficient in the given task.
Cytowania
-
4
CrossRef
-
0
Web of Science
-
4
Scopus
Autorzy (5)
Cytuj jako
Pełna treść
- Wersja publikacji
- Accepted albo Published Version
- DOI:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.15244/pjoes/68151
- Licencja
- otwiera się w nowej karcie
Słowa kluczowe
Informacje szczegółowe
- Kategoria:
- Publikacja w czasopiśmie
- Typ:
- artykuł w czasopiśmie wyróżnionym w JCR
- Opublikowano w:
-
POLISH JOURNAL OF ENVIRONMENTAL STUDIES
nr 26,
strony 1203 - 1214,
ISSN: 1230-1485 - Język:
- angielski
- Rok wydania:
- 2017
- Opis bibliograficzny:
- Redlarski G., Krawczuk M., Kupczyk A., Piechocki J., Ambroziak D.: Swarm-Assisted Investment Planning of a Bioethanol Plant// POLISH JOURNAL OF ENVIRONMENTAL STUDIES. -Vol. 26, nr. 3 (2017), s.1203-1214
- DOI:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.15244/pjoes/68151
- Weryfikacja:
- Politechnika Gdańska
wyświetlono 220 razy