While the use of distributed computing in search and optimization problems has a long research history, most efforts have been devoted to parallel implementations with strict synchronization requirements or to distributed architectures where a central server coordinates the work of clients by partitioning the search space or working as a status repository. In this paper we discuss the distribut...

A new derivative-free global optimization algorithm is proposed for solving nonlinear global optimization problems. It is based on the Branch and Bound (BnB) algorithm. BnB is a general algorithm to solve optimization problems. Its implementation is done by using the developed template library of BnB algorithms. The robustness of the new algorithm is demonstrated by solving a selection of test ...

Boltzmann evolutionary algorithms and their embedded selection mechanisms are traditionally employed to prolong search. After a brief introduction, a precursor called simulated annealing is outlined. A prominent type of Boltzmann evolutionary algorithm called parallel recombinative simulated annealing is then covered in depth. A proof of global convergence for this type of algorithm is illustra...

Pal, S.K ., Genetic algorithms for optimal image enhancement, Pattern Recognition Letters 15 (1994) 261-271 . Genetic algorithms represent a class of highly parallel adaptive search processes for solving a wide range of optimization and machine learning problems . The present work is an attempt to demonstrate their adaptivity and effectiveness for searching global optimal solutions in selecting...

DE algorithm is a population-based heuristic global search technology. The algorithm has simple principle, fewer control parameters, but has strong robustness, and good optimization performance. This paper uses differential evolution algorithm for parameters identification of Wiener model. Firstly, we analyze the influence of mutation rate F on global parallel search ability and convergence in ...

This paper proposes a novel hybrid algorithm namely APSO-BFO which combines merits of Bacterial Foraging Optimization (BFO) algorithm and Adaptive Particle Swarm Optimization (APSO) algorithm to determine the optimal PID parameters for control of nonlinear systems. To balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...

Updating the velocity in particle swarm optimization (PSO) consists of three terms: the inertia term, the cognitive term and the social term. The balance of these terms determines the balance of the global and local search abilities, and therefore the performance of PSO. In this work, an adaptive parallel PSO algorithm, which is based on the dynamic exchange of control parameters between adjace...

PURPOSE To investigate whether exposure to occupational levels of organic solvents in the dry cleaning industry is associated with neurotoxic symptoms and visual deficits in the perception of basic visual features such as luminance contrast and colour, higher level processing of global motion and form (Experiment 1), and cognitive function as measured in a visual search task (Experiment 2). M...