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Metaheuristics in combinatorial optimization
ACM Computing Surveys, 2003The field of metaheuristics for the application to combinatorial optimization problems is a rapidly growing field of research. This is due to the importance of combinatorial optimization problems for the scientific as well as the industrial world. We give a survey of the nowadays most important metaheuristics from a conceptual point of view. We outline
Christian Blum 0001, Andrea Roli
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METAHEURISTIC OPTIMIZATION OF ACOUSTIC INVERSE PROBLEMS
Journal of Computational Acoustics, 2011Swift solving of geoacoustic inverse problems strongly depends on the application of a global optimization scheme. Given a particular inverse problem, this work aims to answer the questions how to select an appropriate metaheuristic search strategy, and how to configure it for optimal performance.
van Leijen, A.V. +2 more
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A Taxonomy of Metaheuristics for Bi-level Optimization
2013In recent years, the application of metaheuristic techniques to solve multilevel and particularly bi-level optimization problems (BOPs) has become an active research area. BOPs constitute a very important class of problems with various applications in different domains. A wide variety of metaheuristics have been proposed in the literature to solve such
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ADVANCES IN METAHEURISTICS FOR HARD OPTIMIZATION
2008In this work, we introduce a new parallel ant colony optimization algorithm based on an ant metaphor and the crossover operator from genetic algorithms.The performance of the proposed model is evaluated usingwell-known numerical test problems and then it is applied to train recurrent neural networks to identify linear and nonlinear dynamic plants.
KALINLI, Adem, Sarıkoç, Fatih
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Metaheuristics for Optimization Problems
2018An introduction to metaheuristics for optimization problems is presented in this chapter. In Sect. 3.1 a classification of metaheuristics is put forward. The metaheuristics Differential Evolution (DE); Particle Collision Algorithm (PCA); Ant Colony Optimization (ACO) in its version for continuous problems; and Particle Swarm Optimization (PSO) are ...
Lídice Camps Echevarría +3 more
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Parameter Meta-optimization of Metaheuristic Optimization Algorithms
2012The quality of a heuristic optimization algorithm is strongly dependent on its parameter values. Finding the optimal parameter values is a laborious task which requires expertise and knowledge about the algorithm, its parameters and the problem. This paper describes, how the optimization of parameters can be automated by using another optimization ...
Christoph Neumüller +3 more
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Overview of metaheuristic optimization
2018Metaheuristic optimization methods have become significant tools and often the only way of solving practical optimization problems. The basic requirement from these methods is to obtain the global solution or a solution close to the global optimum in a reasonable time.
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