Journal of Global Optimization
Convex Optimization
Evolutionary design and applications of hybrid intelligent systems
International Journal of Innovative Computing and Applications
Nature-Inspired Metaheuristic Algorithms
Nature-Inspired Metaheuristic Algorithms
Metaheuristics: From Design to Implementation
Metaheuristics: From Design to Implementation
Boid particle swarm optimisation
International Journal of Innovative Computing and Applications
Firefly algorithm, stochastic test functions and design optimisation
International Journal of Bio-Inspired Computation
Firefly algorithms for multimodal optimization
SAGA'09 Proceedings of the 5th international conference on Stochastic algorithms: foundations and applications
Engineering Optimization: An Introduction with Metaheuristic Applications
Engineering Optimization: An Introduction with Metaheuristic Applications
Multilevel Image Thresholding Selection Based on the Firefly Algorithm
UIC-ATC '10 Proceedings of the 2010 Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing
Bat algorithm for multi-objective optimisation
International Journal of Bio-Inspired Computation
A novel quantum inspired cuckoo search for knapsack problems
International Journal of Bio-Inspired Computation
Mixed variable structural optimization using Firefly Algorithm
Computers and Structures
Classification system using parallel genetic algorithm
International Journal of Innovative Computing and Applications
Multiobjective cuckoo search for design optimization
Computers and Operations Research
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Many inverse problems in engineering can be considered as constrained optimisation, as the aim of inversion is to find the best parameter estimates so as to minimise the differences between the predicted results and the observations while satisfying all known constraints. Such optimisation problems can thus be solved by efficient optimisation techniques. As the number of degrees of freedom is usually very large, metaheuristic algorithms such as Cuckoo Search are particularly suitable for inverse problems, because metaheuristics are very efficient for solving non-linear global optimisation problems. In this paper, we will take a unified approach to inversion and optimisation and introduce a few nature-inspired metaheuristics, including genetic algorithms, differential evolution, firefly algorithm, Cuckoo Search, particle swarm optimisation and their applications in solving inverse problems.