An ACO Algorithm for a Scheduling Problem in Health Simulation Center

2021 ◽  
pp. 333-341
Author(s):  
Simon Caillard ◽  
Corinne Lucet ◽  
Laure Brisoux-Devendeville
Keyword(s):  
Scheduling Problem ◽  
Simulation Center ◽  
Health Simulation

Needed: A National Security Simulation Center

2008 ◽  
Author(s):  
Rachel K. Hanig ◽  
Mark E. Henshaw
Keyword(s):  
National Security ◽  
Simulation Center

Improving the solution complexity of the scheduling problem with deadlines: A general technique

2016 ◽  
Vol 50 (4-5) ◽  
pp. 681-687
Author(s):  
Amir Elalouf ◽  
Eugene Levner
Keyword(s):  
Scheduling Problem ◽  
General Technique

Optimal broadcast scheduling method for VANETs: An adaptive discrete firefly approach

2020 ◽  
Vol 39 (6) ◽  
pp. 8125-8137
Author(s):  
Jackson J Christy ◽  
D Rekha ◽  
V Vijayakumar ◽  
Glaucio H.S. Carvalho
Keyword(s):  
Intelligent Transportation System ◽  
Search Algorithm ◽  
Mac Protocol ◽  
High Mobility ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Traffic Density ◽  
Scheduling Problem ◽  
Broadcast Scheduling

Vehicular Adhoc Networks (VANET) are thought-about as a mainstay in Intelligent Transportation System (ITS). For an efficient vehicular Adhoc network, broadcasting i.e. sharing a safety related message across all vehicles and infrastructure throughout the network is pivotal. Hence an efficient TDMA based MAC protocol for VANETs would serve the purpose of broadcast scheduling. At the same time, high mobility, influential traffic density, and an altering network topology makes it strenuous to form an efficient broadcast schedule. In this paper an evolutionary approach has been chosen to solve the broadcast scheduling problem in VANETs. The paper focusses on identifying an optimal solution with minimal TDMA frames and increased transmissions. These two parameters are the converging factor for the evolutionary algorithms employed. The proposed approach uses an Adaptive Discrete Firefly Algorithm (ADFA) for solving the Broadcast Scheduling Problem (BSP). The results are compared with traditional evolutionary approaches such as Genetic Algorithm and Cuckoo search algorithm. A mathematical analysis to find the probability of achieving a time slot is done using Markov Chain analysis.

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