AICTE-ISTE Sponsored STTP On Metaheuristics : Emerging Paradigm in Engineering Optimization & Facult (METAHEURISTICS & FAC)
|Event Date/Time: Jun 23, 2008||End Date/Time: Jun 30, 2008|
|Registration Date: Jun 12, 2008|
|Early Registration Date: Jun 09, 2008|
Recently, much progress has been made in finding exact (provably optimal) solutions to some combinatorial optimization problems. But these are still not solved exactly and require good heuristic methods. Moreover, reaching "optimal solutions" is in many cases meaningless, as in practice we are often dealing with models that are rough simplifications of reality. The aim of heuristic methods for combinatorial optimization is to quickly produce good-quality solutions, without necessarily providing any guarantee of solution quality.
Metaheuristics are high level procedures that coordinate simple heuristics, such as local search, to find solutions that are of better quality than those found by the simple heuristics alone. Modern metaheuristics have proved to be effective and efficient approaches, being flexible to accommodate variations in problem structure and in the objectives considered for the evaluation of solutions. For all these reasons, metaheuristics have probably been one of the most stimulating research topics in optimization for the last two decades.
The topics include:
â€¢ Simulated annealing
â€¢ Genetic algorithm
â€¢ Artificial Neural Network
â€¢ Particle Swarm Optimizatiom
â€¢ Tabu search
â€¢ Ant colony optimization
â€¢ Variable neighborhood search and their hybrids.