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A Multi-objective GRASP Algorithm for Joint Optimization of Energy Consumption and Schedule Length of Precedence-Constrained Applications
"... Abstract—We address the problem of scheduling precedenceconstrained scientific applications on a heterogeneous distributed processor system with the twin objectives of minimizing simultaneously energy consumption and schedule length. Previous research efforts on scheduling have focused on the minimi ..."
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Abstract—We address the problem of scheduling precedenceconstrained scientific applications on a heterogeneous distributed processor system with the twin objectives of minimizing simultaneously energy consumption and schedule length. Previous research efforts on scheduling have focused on the minimization of a quality of service metric based on the completion time of applications (e.g., the schedule length). Recently, many researchers are working on the design of new scheduling algorithms that consider the minimization of energy consumption. We report a new scheduling algorithm accounting for both objectives. The new scheduling algorithm is based on a multi-start randomized adaptive search technique (GRASP framework) that adopts Dynamic Voltage Scaling technique to minimize energy consumption. This technique enables processors to operate in different voltage supply levels at the cost of sacrificing clock frequencies. This multiple voltage implies a trade-off between the quality of the schedules and energy consumption. Therefore, the new proposed approach is designed as a multi-objective algorithm that simultaneously optimize both objectives. Simulation results on a set of realworld applications emphasize the robust performance of the proposed approach.
A nonmonotone GRASP
, 2014
"... A Greedy Randomized Adaptive Search Procedure (GRASP) is an iterative multistart meta-heuristic for difficult combinatorial optimization problems. Each GRASP iteration consists of two phases: a construction phase, in which a feasible solution is produced, and a local search phase, in which a local o ..."
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A Greedy Randomized Adaptive Search Procedure (GRASP) is an iterative multistart meta-heuristic for difficult combinatorial optimization problems. Each GRASP iteration consists of two phases: a construction phase, in which a feasible solution is produced, and a local search phase, in which a local optimum in the neighborhood of the constructed solution is sought. Repeated applications of the construction procedure yields different starting solutions for the local search and the best overall solution is kept as the result. The GRASP local search applies iterative improvement until a locally optimal solution is found. During this phase, starting from the current solution an improving neighbor solution is accepted and considered as new current solution. In this paper, we propose a variant of the GRASP framework that uses a new “nonmonotone” strategy to explore the neighborhood of the current solution. We formally state the convergence of the nonmonotone local search to a locally optimal solution and illustrate the effectiveness of the resulting Nonmonotone GRASP on the Maximum Cut Problem, a classical hard combinatorial optimization problem.
Scatter search for an uncapacitated p-hub median problem
, 2014
"... Scatter search is a population-based method that has been shown to yield high-quality outcomes for combinatorial optimization problems. It uses strategies for combining solution vectors that have proved effective in a variety of problem settings. In this paper, we present a scatter search implementa ..."
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Scatter search is a population-based method that has been shown to yield high-quality outcomes for combinatorial optimization problems. It uses strategies for combining solution vectors that have proved effective in a variety of problem settings. In this paper, we present a scatter search implementation for an NP-hard variant of the classic p-hub median prob-lem. Specifically, we tackle the uncapacitated r-allocation p-hub median problem, which consists of minimizing the cost of transporting the traffics between nodes of a network through special facilities that act as trans-shipment points. This problem has a significant number of applications in practice, such as the design of transportation and telecommunications networks. As it is customary in metaheuristic implementations, we design spe-cific methods to create an efficient solving procedure based on the scatter search methodology. In particular, we propose mechanisms to generate, combine, and improve solutions for this problem. Special mention de-serves the use of path-relinking as an extension of the classical combination method. Extensive computational experiments establish the effectiveness of our procedure in relation to approaches previously identified to be best.
Composition du jury
"... présentée et soutenue publiquement le.. septembre 2011 en vue de l’obtention du Doctorat de l’Université d’Artois (Spécialité: Génie Informatique et Automatique) par ..."
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présentée et soutenue publiquement le.. septembre 2011 en vue de l’obtention du Doctorat de l’Université d’Artois (Spécialité: Génie Informatique et Automatique) par
