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  • T V Luong
  • 2003
Helminths or worm infestations refer to worms that live as parasites in the human body and are a fundamental cause of disease associated with health and nutrition problems beyond gastrointestinal tract disturbances. Globally, over 3.5 billion people are infected with intestinal worms, of which 1.47 billion are with roundworm, 1.3 billion people with(More)
The island model for evolutionary algorithms allows to delay the global convergence of the evolution process and encourage diversity. However, solving large size and time-intensive combinatorial optimization problems with the island model requires a large amount of computational resources. GPU computing is recently revealed as a powerful way to harness(More)
The quadratic 3-dimensional assignment problem (Q3AP) is an extension of the well-known NP-hard quadratic assignment problem. It has been proved to be one of the most difficult combinatorial optimization problems. Local search (LS) algorithms are a class of heuristics which have been successfully applied to solve such hard optimization problem. These(More)
Local search (LS) algorithms are among the most powerful techniques for solving computationally hard problems in combinatorial optimization. These algorithms could be viewed as ¿walks through neighborhoods¿ where the walks are performed by iterative procedures that allow to move from a solution to another one in the solution space. In these heuristics,(More)
Establishing the current status and distribution of soil-transmitted helminths is essential for developing and implementing parasite control. Although Southeast Asia is known to have a high prevalence of infection, a precise estimate of the total disease burden has not been fully described. Here, we use Geographical Information Systems (GIS) to collate and(More)
—Local search metaheuristics (LSMs) are efficient methods for solving complex problems in science and industry. They allow significantly to reduce the size of the search space to be explored and the search time. Nevertheless, the resolution time remains prohibitive when dealing with large problem instances. Therefore, the use of GPU-based massively parallel(More)
— Over the last years, interest in hybrid meta-heuristics has risen considerably in the field of optimization. Combinations of methods such as evolutionary algorithms and local searches have provided very powerful search algorithms. However, due to their complexity, the computational time of the solution search exploration remains exorbitant when large(More)
Optimization problems are more and more complex and their resource requirements are ever increasing. Although metaheuristics allow to significantly reduce the computational complexity of the search process , the latter remains time-consuming for many problems in diverse domains of application. As a result, the use of GPU has been recently revealed as an(More)
Local search (LS) algorithms are among the most powerful techniques for solving com-putationally hard problems in combinatorial optimization. These algorithms could be viewed as " walks through neighborhoods " where the walks are performed by iterative procedures that allow to move from a solution to another one in the solution space. In these heuristics,(More)