Add to ORKGInterest on dynamic multimodal functions risen over the last years since many real problems have this feature. On these problems, the goal is no longer to find the global optimal, but to track their progression through the space as closely as possible. This paper presents three evolutionary algorithms for dynamic fitness landscapes. In order to mantain diversity in the population they use two clustering techniques and a macromutation operator. Besides, this paper compares two crossover operators: arithmetic and multiparents two points, respectively. Effectiveness and limitations of each algorithm are discuss and analyzed.Fil: Aragon, Victoria Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico ...
2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR) : 13 Nov-15 Nov...
This work presents a new hybrid approach for supporting sequential niching strategies called Cluster...
In model-based evolutionary algorithms (EAs), the underlying search distribution is adapted to the p...
Interest of dynamic multimodal functions risen over the last year since many real problems have this...
Non-stationary, or dynamic, problems change over time. There exist a variety of forms of dynamism. T...
Summary. Solving multimodal optimization tasks (problems with multiple glo-bal/local optimal solutio...
Present paper introduces a new evolutionary technique for multimodal real-valued optimization which ...
The problem of locating all the optima within a multi-modal fitness landscape has been widely addres...
To solve dynamic optimization problems, multiple population methods are used to enhance the populati...
To solve dynamic optimization problems, multiple population methods are used to enhance the populati...
This paper presents a survey of evolutionary algorithms designed for clustering tasks. It tries to r...
Non-stationary, or dynamic, problems change over time. There exist a variety of forms of dynamism. T...
Copyright @ 2011 IEEETo solve dynamic optimization problems, multiple population methods are used t...
Many optimization functions have complex landscapes with multiple global or local optima. In order t...
Niche formation allows evolutionary algorithms to be used when the location and maintenance of multi...
2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR) : 13 Nov-15 Nov...
This work presents a new hybrid approach for supporting sequential niching strategies called Cluster...
In model-based evolutionary algorithms (EAs), the underlying search distribution is adapted to the p...
Interest of dynamic multimodal functions risen over the last year since many real problems have this...
Non-stationary, or dynamic, problems change over time. There exist a variety of forms of dynamism. T...
Summary. Solving multimodal optimization tasks (problems with multiple glo-bal/local optimal solutio...
Present paper introduces a new evolutionary technique for multimodal real-valued optimization which ...
The problem of locating all the optima within a multi-modal fitness landscape has been widely addres...
To solve dynamic optimization problems, multiple population methods are used to enhance the populati...
To solve dynamic optimization problems, multiple population methods are used to enhance the populati...
This paper presents a survey of evolutionary algorithms designed for clustering tasks. It tries to r...
Non-stationary, or dynamic, problems change over time. There exist a variety of forms of dynamism. T...
Copyright @ 2011 IEEETo solve dynamic optimization problems, multiple population methods are used t...
Many optimization functions have complex landscapes with multiple global or local optima. In order t...
Niche formation allows evolutionary algorithms to be used when the location and maintenance of multi...
2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR) : 13 Nov-15 Nov...
This work presents a new hybrid approach for supporting sequential niching strategies called Cluster...
In model-based evolutionary algorithms (EAs), the underlying search distribution is adapted to the p...