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Artificial immune systems (AIS) represent a family of bio-inspired populational meta-heuristic algorithms successful in solving complex problems. Combinatorial optimization problems constitute a class of problems with a discrete set of solutions. In this study we provide an initial evaluation of the practical results of AIS for two well known combinatorial optimization problems — the linear ordering...
Scheduling is one of the core steps to efficiently exploit the capabilities of heterogeneous distributed computing systems and it is also an appealing NP-complete problem. There is a number of heuristic and metaheuristic algorithms that were tailored to deal with scheduling of independent jobs. In this study we investigate the efficiency of three bio-inspired metaheuristics for finding good schedules...
The recent time has seen the rise of consumer grade massively parallel environments. Powerful GPUs and multi-core processors became widely available and easy to use programming APIs such as nVidia CUDA, OpenCL, and DirectCompute simplify the development of applications that can utilize them. In this environment, the nature inspired meta-heuristics can be in suitable cases implemented in parallel without...
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