53,296 research outputs found

    Algorithms Applied to Global Optimisation – Visual Evaluation

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    Evaluation and assessment of various search and optimisation algorithms is subject of large research efforts. Particular interest of this study is global optimisation and presented approach is based on observation and visual evaluation of Real-Coded Genetic Algorithm, Particle Swarm Optimisation, Differential Evolution and Free Search, which are briefly described and used for experiments. 3D graphical views, generated by visualisation tool VOTASA, illustrate essential aspects of global search process such as divergence, convergence, dependence on initialisation and utilisation of accidental events. Discussion on potential benefits of visual analysis, supported with numerical results, which could be used for comparative assessment of other methods and directions for further research conclude presented study

    Freeze-drying modeling and monitoring using a new neuro-evolutive technique

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    This paper is focused on the design of a black-box model for the process of freeze-drying of pharmaceuticals. A new methodology based on a self-adaptive differential evolution scheme is combined with a back-propagation algorithm, as local search method, for the simultaneous structural and parametric optimization of the model represented by a neural network. Using the model of the freeze-drying process, both the temperature and the residual ice content in the product vs. time can be determine off-line, given the values of the operating conditions (the temperature of the heating shelf and the pressure in the drying chamber). This makes possible to understand if the maximum temperature allowed by the product is trespassed and when the sublimation drying is complete, thus providing a valuable tool for recipe design and optimization. Besides, the black box model can be applied to monitor the freeze-drying process: in this case, the measurement of product temperature is used as input variable of the neural network in order to provide in-line estimation of the state of the product (temperature and residual amount of ice). Various examples are presented and discussed, thus pointing out the strength of the too

    Adaptive multimodal continuous ant colony optimization

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    Seeking multiple optima simultaneously, which multimodal optimization aims at, has attracted increasing attention but remains challenging. Taking advantage of ant colony optimization algorithms in preserving high diversity, this paper intends to extend ant colony optimization algorithms to deal with multimodal optimization. First, combined with current niching methods, an adaptive multimodal continuous ant colony optimization algorithm is introduced. In this algorithm, an adaptive parameter adjustment is developed, which takes the difference among niches into consideration. Second, to accelerate convergence, a differential evolution mutation operator is alternatively utilized to build base vectors for ants to construct new solutions. Then, to enhance the exploitation, a local search scheme based on Gaussian distribution is self-adaptively performed around the seeds of niches. Together, the proposed algorithm affords a good balance between exploration and exploitation. Extensive experiments on 20 widely used benchmark multimodal functions are conducted to investigate the influence of each algorithmic component and results are compared with several state-of-the-art multimodal algorithms and winners of competitions on multimodal optimization. These comparisons demonstrate the competitive efficiency and effectiveness of the proposed algorithm, especially in dealing with complex problems with high numbers of local optima

    Meta-dynamical adaptive systems and their applications to a fractal algorithm and a biological model

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    In this article, one defines two models of adaptive systems: the meta-dynamical adaptive system using the notion of Kalman dynamical systems and the adaptive differential equations using the notion of variable dimension spaces. This concept of variable dimension spaces relates the notion of spaces to the notion of dimensions. First, a computational model of the Douady's Rabbit fractal is obtained by using the meta-dynamical adaptive system concept. Then, we focus on a defense-attack biological model described by our two formalisms

    Comparison of Evolutionary Optimization Algorithms for FM-TV Broadcasting Antenna Array Null Filling

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    Broadcasting antenna array null filling is a very challenging problem for antenna design optimization. This paper compares five antenna design optimization algorithms (Differential Evolution, Particle Swarm, Taguchi, Invasive Weed, Adaptive Invasive Weed) as solutions to the antenna array null filling problem. The algorithms compared are evolutionary algorithms which use mechanisms inspired by biological evolution, such as reproduction, mutation, recombination, and selection. The focus of the comparison is given to the algorithm with the best results, nevertheless, it becomes obvious that the algorithm which produces the best fitness (Invasive Weed Optimization) requires very substantial computational resources due to its random search nature

    HEURISTICS OPTIMISATION OF NUMERICAL FUNCTIONS

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    The article presents an investigation of heuristic behaviour of search algorithms applied to numerical problems. The aim is to compare the abilities of Particle Swarm Optimisation, Differential Evolution and Free Search to adapt to variety of search spaces without the need for constant re-tuning of algorithms parameters. The article focuses on several advanced characteristics of Free Search and attempts to clarify specifics of its behaviour. The achieved experimental results are presented and discussed
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