Adaptive SAGA Based on Mutative Scale Chaos Optimization Strategy
نویسندگان
چکیده
منابع مشابه
The Strategy Logic Saga
In open-system verification, a fundamental area of research is the study of modal logics for strategic reasoning in the setting of multi-agent games [3, 5]. An important contribution in this field has been the development of Alternating-Time Temporal Logic (ATL∗, for short), introduced by Alur, Henzinger, and Kupferman [1]. Formally, it is obtained as a generalization of the logic CTL∗ [4], whe...
متن کاملThe WSN Coverage Optimization of the Diversified AFSA Based on Chaos Learning Strategy
WSN coverage optimization is an important problem. Considering that the artificial fish algorithm is easy to fall into local optimum and of slow convergence, an improved algorithm has been proposed in this paper. The chaos strategy is used to carry out the initialization of the foraging behavior, which makes the fish swarm evenly distributed in space, to avoid the randomness of the initialized ...
متن کاملNovel Mutative Particle Swarm Optimization Algorithm for Discrete Optimization
Mutative Particle Swarm Optimization (MPSO) is swarm-based stochastic optimization algorithm combined with the mutative function inspired by Genetic Algorithm (GA). The algorithm searches for the solution by combining swarming behavior, as well as mutation of the particles to accelerate the search process. This paper presents a modification to the MPSO algorithm for it to solve Integer Programm...
متن کاملAdaptive Learning Rate Elitism Estimation of Distribution Algorithm Combining Chaos Perturbation for Large Scale Optimization
Estimation of distribution algorithm (EDA) is a kind of EAs, which is based on the technique of probabilistic model and sampling. Large scale optimization problems are a challenge for the conventional EAs. This paper presents an adaptive learning rate elitism EDA combining chaos perturbation (ALREEDA) to improve the performance of traditional EDA to solve high dimensional optimization problems....
متن کاملResearch on Fuzzy Adaptive Optimization Strategy of Particle Swarm Algorithm
This paper introduces a novel fuzzy adaptive optimization strategy (FAOPSO) for the particle swarm algorithm. Initially, to avoid falling into local optimums, the information of multioptimum distribution state is introduced into the particle swarm movement programming. However, in this kind of multi-optimum static programming mode (MSPPSO), the programming proportion factor of multi-optimum can...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Information Technology Journal
سال: 2006
ISSN: 1812-5638
DOI: 10.3923/itj.2006.524.528