Stefka Fidanova Institute for Information and Communication Technologies
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Transcript of Stefka Fidanova Institute for Information and Communication Technologies
Ant Algorithm and its Applications for Solving Large Scale Optimization
Problems on Parallel Computers
Stefka FidanovaInstitute for Information and
Communication TechnologiesBulgarian Academy of Sciences
Hard Optimization Problems
• Vehicle routing problem
• Decision making problem
• Cutting stock problem
• Sensor layout problem
• GPS surveying problem
• Multidimensional surface global optimum
Metaheuristics
• A metaheuristics are methods for solving a very general class of computational problems by combining user-given black-box procedures in the hope of obtaining a more efficient or more robust procedure. The name combines the Greek prefix "meta" ("beyond", here in the sense of "higher level") and "heuristic" (from ευρισκειν, heuriskein, "to find").
• Metaheuristics are generally applied to problems for which there is no satisfactory problem-specific algorithm or heuristic; or when it is not practical to implement such a method. Most commonly used metaheuristics are targeted to combinatorial optimization problems, but of course can handle any problem that can be recast in that form, such as solving boolean equations
Metaheuristics Methods
• Genetic algorithm
• Simulated annealing
• Tabu search
• Ant colony optimization
• Particle swarm optimization
Ant Colony Optimization
Ant Colony OptimizationProcedure ACOBegin
initialize the pheromonewhile stopping criterion not satisfied do
position each ant on a starting noderepeat
for each ant dochose next node
end foruntil every ant has build a solutionupdate the pheromone
end whileend
Level of Parallelism
• Problem division to subproblems
• Several ant colonies communicates after every iteration
• Several ant colonies without communications
Problem Division to Subproblems
1
2
3
4
Ant Colonies with communications
Ant Colonies without communications
Examples
• Sensor layout problem
• Global optimum on multidimensional surface
Wireless Sensor Network
• Reconnaissance
• Surveillance
• Forest fire prevention
• Volcano eruption study
• Health data monitoring
• Civil engineering
WSN Layout Problem
• High Energy Communication Node
• Sensing Radius
• Communication Radius
• Fully Covered and Connected Area
• Minimal Number of Sensors
Sensor Layout Problem
• Ant colonies without communications
Global Optimum on Multidimensional Surface
Global Optimum on Multidimensional Surface
• Surface decomposition
• 4 ant colonies on one processor
• Several colonies without communications
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