Pregled bibliografske jedinice broj: 687794
Optimization of Waterway with Multiple Locks and Canals by Integration of Petri Net and Genetic Algorithm
Optimization of Waterway with Multiple Locks and Canals by Integration of Petri Net and Genetic Algorithm // Journal of mathematics and system science, 3 (2013), 12; 577-591 (podatak o recenziji nije dostupan, članak, znanstveni)
CROSBI ID: 687794 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Optimization of Waterway with Multiple Locks and Canals by Integration of Petri Net and Genetic Algorithm
Autori
Gudelj, Anita ; Kezić, Danko
Izvornik
Journal of mathematics and system science (2159-5291) 3
(2013), 12;
577-591
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Waterway traffic system; optimization; deadlock avoidance; genetic algorithm; Petri net
Sažetak
His paper presents the possibilities of job optimization in waterway with multiple locks and canals, in order to increase the system productivity. Safe navigation in such complex waterway system is very demanding. Some of the problems that need to be solved are: How to control traffic in a way that vessels move in opposite directions ; How to resolve possible conflicts in case that more vessels try to acquire particular lock at the same time ; How to avoid possible deadlocks ; How to ensure the vessel passage in the shortest possible time? It is necessary to apply adequate control policy to avoid deadlocks and blocks the vessels’ moving only in the case of dangerous situation. The motion of vessels can be described as the set of discrete events and states. Herein we propose deadlock avoidance algorithm for complex waterway system with multiple key resources and we use multiple re- entrant flowlines class of Petri net (MRF1PN). The solution represents deadlock prevention supervisor in a sense that vessels are stopped only in a case of immediate dangerous situation in dense traffic. The goal of this paper is to find optimal, conflict and deadlock free job schedule in CWS. In this sense, the authors developed the algorithm which integrates MRF1PN with a genetic algorithm. The algorithm deals with multi-constrained scheduling problem with shared resources. The final goals are minimization the total travel time of vessels through the waterway system.
Izvorni jezik
Engleski
Znanstvena područja
Tehnologija prometa i transport, Informacijske i komunikacijske znanosti
POVEZANOST RADA
Projekti:
036-0363078-3018 - Upravljanje mobilnim robotima i vozilima u nepoznatim i dinamičkim okruženjima (Petrović, Ivan, MZO ) ( CroRIS)
Ustanove:
Pomorski fakultet, Split
Citiraj ovu publikaciju:
Uključenost u ostale bibliografske baze podataka::
- Database of EBSCO, Massachusetts, USA
- CSA Technology Research Database
- Ulrich’s Periodicals Directory
- Index Copernicus, Poland
- Norwegian Social Science Data Services (NSD), Database for Statistics on Higher Education (DBH), Norway
- Summon Serials Solutions
- Chinese Database of CEPS, Airiti Inc. & OCLC
- Chinese Scientific Journals Database, VIP Corporation, Chongqing, P. R. China
- Google schol