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Kosmos
Astronomia Astrofizyka
Inne

Kultura
Sztuka dawna i współczesna, muzea i kolekcje

Metoda
Metodologia nauk, Matematyka, Filozofia, Miary i wagi, Pomiary

Materia
Substancje, reakcje, energia
Fizyka, chemia i inżynieria materiałowa

Człowiek
Antropologia kulturowa Socjologia Psychologia Zdrowie i medycyna

Wizje
Przewidywania Kosmologia Religie Ideologia Polityka

Ziemia
Geologia, geofizyka, geochemia, środowisko przyrodnicze

Życie
Biologia, biologia molekularna i genetyka

Cyberprzestrzeń
Technologia cyberprzestrzeni, cyberkultura, media i komunikacja

Działalność
Wiadomości | Gospodarka, biznes, zarządzanie, ekonomia

Technologie
Budownictwo, energetyka, transport, wytwarzanie, technologie informacyjne

Planning and Optimization of AGV Jobs by Petri Net and Genetic Algorithm

The following article presents the possibilities of job optimization on a maritime container terminal, in order to increase the system productivity and optimize the terminal capacity. Automated guided vehicles (AGVs) are now becoming popular mode of container transport in seaport terminals. The moving of vehicles can be described as the set of discrete events and states. Some of these states can be undesirable such as conflicts and deadlocks. It is necessary to apply adequate control policy to avoid deadlocks and block the vehicles’ moving only in the case of dangerous situation.This paper addresses the use a Petri net as modeling and scheduling tool in this context. The aim of AGV scheduling is to dispatch a set of AGVs to improve the productivity of a system and reduce delay in a batch of pickup/drop-off jobs under certain constraints such as deadlines, priority, etc. The final goals are related to optimization of processing time and minimization of the number of AGVs involved while maintaining the system throughput.To find better solutions, the authors propose the integration MRF1 class of Petri net (MRF1PN) with a genetic algorithm. Also, the use of a matrix based formal method is proposed to analyze discrete event dynamic system (DEDS). The algorithm is described to deal with multi-project, multi-constrained scheduling problem with shared resources. The developed model was tested and validated by simulation of typical scenarios of the container terminal of Port Koper. Modularity and simplicity of the approach allow using the model to monitor and test the efficiency of the processes, and also to propose future alternative solutions to optimize the schedule of operations and the employment of AGV at the terminal.