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» A Heuristic for Nonlinear Global Optimization
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AIPS
2006
13 years 10 months ago
Exploiting the Power of Local Search in a Branch and Bound Algorithm for Job Shop Scheduling
This paper presents three techniques for using an iterated local search algorithm to improve the performance of a state-of-the-art branch and bound algorithm for job shop scheduli...
Matthew J. Streeter, Stephen F. Smith
VEE
2009
ACM
172views Virtualization» more  VEE 2009»
14 years 3 months ago
Entropy: a consolidation manager for clusters
Clusters provide powerful computing environments, but in practice much of this power goes to waste, due to the static allocation of tasks to nodes, regardless of their changing co...
Fabien Hermenier, Xavier Lorca, Jean-Marc Menaud, ...
GECCO
2007
Springer
176views Optimization» more  GECCO 2007»
14 years 2 months ago
Two-level of nondominated solutions approach to multiobjective particle swarm optimization
In multiobjective particle swarm optimization (MOPSO) methods, selecting the local best and the global best for each particle of the population has a great impact on the convergen...
M. A. Abido
GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
14 years 10 days ago
Genetic algorithms for positioning and utilizing sensors in synthetically generated landscapes
Positioning multiple sensors for acquisition of a a given environment is one of the fundamental research areas in various fields, such as military scouting, computer vision and ro...
Haluk Topcuoglu, Murat Ermis
GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
14 years 10 days ago
Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach
This work describes a forward-looking approach for the solution of dynamic (time-changing) problems using evolutionary algorithms. The main idea of the proposed method is to combi...
Iason Hatzakis, David Wallace