On solving the unrelated parallel machine scheduling problem: active microrheology as a case study
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Orts Gómez, Francisco José; Ortega López, Gloria; Puertas López, Antonio Manuel; García Fernández, Inmaculada; Martín Garzón, Gracia EsterDate
2020-02-02Abstract
Modern computational platforms are characterized by the heterogeneity of their processing elements. Additionally, there are many algorithms which can be structured as a set of procedures or tasks with different computational cost. Balancing the computational load among the available processing elements is one of the main keys for the optimal exploitation of such heterogeneous platforms. When the processing time of any procedure executed on any of the available processing elements is known, this workload-balancing problem can be modeled as the well-known scheduling on unrelated parallel machines problem. Solving this type of problems is a big challenge due to the high heterogeneity on both, the tasks and the machines. In this paper, the balancing problem has been formally defined as a global optimization problem which minimizes the makespan (parallel runtime) and a heuristic based on a Genetic Algorithm, called Genetic Scheduler (GenS), has been developed to solve it. In order to analyz...