A collection of test problems for constrained global optimization algorithms
A collection of test problems for constrained global optimization algorithms
Swarm intelligence
Simulated Annealing: A Proof of Convergence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Convergence Analysis of Simulated Annealing-Based Algorithms Solving Flow Shop Scheduling Problems
CIAC '00 Proceedings of the 4th Italian Conference on Algorithms and Complexity
Metaheuristics in combinatorial optimization: Overview and conceptual comparison
ACM Computing Surveys (CSUR)
Fundamentals of Computational Swarm Intelligence
Fundamentals of Computational Swarm Intelligence
Lévy flights, non-local search and simulated annealing
Journal of Computational Physics
Nature-Inspired Metaheuristic Algorithms
Nature-Inspired Metaheuristic Algorithms
Nonlinear inertia weight variation for dynamic adaptation in particle swarm optimization
Computers and Operations Research
Continuous Lunches Are Free Plus the Design of Optimal Optimization Algorithms
Algorithmica - Including a Special Section on Genetic and Evolutionary Computation; Guest Editors: Benjamin Doerr, Frank Neumann and Ingo Wegener
Metaheuristics: From Design to Implementation
Metaheuristics: From Design to Implementation
Firefly algorithm, stochastic test functions and design optimisation
International Journal of Bio-Inspired Computation
Engineering Optimization: An Introduction with Metaheuristic Applications
Engineering Optimization: An Introduction with Metaheuristic Applications
Bioinspired Computation in Combinatorial Optimization: Algorithms and Their Computational Complexity
Bioinspired Computation in Combinatorial Optimization: Algorithms and Their Computational Complexity
Theory of Randomized Search Heuristics: Foundations and Recent Developments
Theory of Randomized Search Heuristics: Foundations and Recent Developments
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
Adaptive search with stochastic acceptance probabilities for global optimization
Operations Research Letters
A hybrid CS/PSO algorithm for global optimization
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part III
A hybrid ICA/PSO algorithm by adding independent countries for large scale global optimization
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part III
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Metaheuristic algorithms are becoming an important part of modern optimization. A wide range of metaheuristic algorithms have emerged over the last two decades, and many metaheuristics such as particle swarm optimization are becoming increasingly popular. Despite their popularity, mathematical analysis of these algorithms lacks behind. Convergence analysis still remains unsolved for the majority of metaheuristic algorithms, while efficiency analysis is equally challenging. In this paper, we intend to provide an overview of convergence and efficiency studies of metaheuristics, and try to provide a framework for analyzing metaheuristics in terms of convergence and efficiency. This can form a basis for analyzing other algorithms. We also outline some open questions as further research topics.