Advances in Metaheuristics Luca
نویسندگان
چکیده
We reconsider stochastic convergence analyses of particle swarm optimisation, and point out that previously obtained parameter conditions are not always sufficient to guarantee mean square convergence to a local optimum. We show that stagnation can in fact occur for non-trivial configurations in non-optimal parts of the search space, even for simple functions like SPHERE. The convergence properties of the basic PSO may in these situations be detrimental to the goal of optimisation, to discover a sufficiently good solution within reasonable time. To characterise optimisation ability of algorithms, we suggest the expected first hitting time (FHT), i.e., the time until a search point in the vicinity of the optimum is visited. It is shown that a basic PSO may have infinite expected FHT, while an algorithm introduced here, the Noisy PSO, has finite expected FHT on some functions.
منابع مشابه
Advances in Metaheuristics for Hard Optimization
Springer ISBN-10: 3642092063 ISBN-13: 978-3642092060 Paperback 481 pages 2010 Many advances have been made recently in metaheuristic methods, from theory to applications. The community of researchers claiming the relevance of their work to the field of metaheuristics is growing faster and faster, despite the fact that the term itself has not been precisely defined. Numerous books have been publ...
متن کاملMetaheuristics in Stochastic Combinatorial Optimization: a Survey
Metaheuristics such as Ant Colony Optimization, Evolutionary Computation, Simulated Annealing, Tabu Search and Stochastic Partitioning Methods are introduced, and their recent applications to a wide class of combinatorial optimization problems under uncertainty are reviewed. The flexibility of metaheuristics in being adapted to different modeling approaches and problem formulations emerges clea...
متن کاملParallel metaheuristics: recent advances and new trends
The field of parallel metaheuristics is continuously evolving as a result of new technologies and needs that researchers have been encountering. In the last decade, new models of algorithms, new hardware for parallel execution/communication, and new challenges in solving complex problems have been making advances in a fast manner. We aim to discuss here on the state of the art, in a summarized ...
متن کاملA Comparison of the Performance of Different Metaheuristics on the Timetabling Problem
The main goal of this paper is to attempt an unbiased comparison of the performance of straightforward implementations of five different metaheuristics on a university course timetabling problem. In particular, the metaheuristics under consideration are Evolutionary Algorithms, Ant Colony Optimization, Iterated Local Search, Simulated Annealing, and Tabu Search. To attempt fairness, the impleme...
متن کامل