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Approximating the nondominated front using the Pareto Archived Evolution Strategy
 EVOLUTIONARY COMPUTATION
, 2000
"... We introduce a simple evolution scheme for multiobjective optimization problems, called the Pareto Archived Evolution Strategy (PAES). We argue that PAES may represent the simplest possible nontrivial algorithm capable of generating diverse solutions in the Pareto optimal set. The algorithm, in its ..."
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Cited by 321 (19 self)
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We introduce a simple evolution scheme for multiobjective optimization problems, called the Pareto Archived Evolution Strategy (PAES). We argue that PAES may represent the simplest possible nontrivial algorithm capable of generating diverse solutions in the Pareto optimal set. The algorithm, in its
From recombination of genes to the estimation of distributions I. binary parameters
, 1996
"... The Breeder Genetic Algorithm (BGA) is based on the equation for the response to selection. In order to use this equation for prediction, the variance of the fitness of the population has to be estimated. For the usual sexual recombination the computation can be difficult. In this paper we shortly ..."
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Cited by 312 (9 self)
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The Breeder Genetic Algorithm (BGA) is based on the equation for the response to selection. In order to use this equation for prediction, the variance of the fitness of the population has to be estimated. For the usual sexual recombination the computation can be difficult. In this paper we
An Efficient Constraint Handling Method for Genetic Algorithms
 Computer Methods in Applied Mechanics and Engineering
, 1998
"... Many realworld search and optimization problems involve inequality and/or equality constraints and are thus posed as constrained optimization problems. In trying to solve constrained optimization problems using genetic algorithms (GAs) or classical optimization methods, penalty function methods hav ..."
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Cited by 246 (19 self)
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Many realworld search and optimization problems involve inequality and/or equality constraints and are thus posed as constrained optimization problems. In trying to solve constrained optimization problems using genetic algorithms (GAs) or classical optimization methods, penalty function methods
Using dual approximation algorithms for scheduling problems: theoretical and practical results
 Journal of the ACM
, 1987
"... Abstract. The problem of scheduling a set of n jobs on m identical machines so as to minimize the makespan time is perhaps the most wellstudied problem in the theory of approximation algorithms for NPhard optimization problems. In this paper the strongest possible type of result for this problem, ..."
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Cited by 216 (2 self)
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Abstract. The problem of scheduling a set of n jobs on m identical machines so as to minimize the makespan time is perhaps the most wellstudied problem in the theory of approximation algorithms for NPhard optimization problems. In this paper the strongest possible type of result for this problem
PerformanceEffective and LowComplexity Task Scheduling for Heterogeneous Computing
 IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
, 2002
"... Efficient application scheduling is critical for achieving high performance in heterogeneous computing environments. The application scheduling problem has been shown to be NPcomplete in general cases as well as in several restricted cases. Because of its key importance, this problem has been exte ..."
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Cited by 255 (0 self)
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with the related work, a parametric graph generator was designed to generate weighted directed acyclic graphs with various characteristics. The comparison study, based on both randomly generated graphs and the graphs of some real applications, shows that our scheduling algorithms significantly surpass previous
Removing The Genetics from The Standard Genetic Algorithm
 In Proceedings of ICML’95
, 1995
"... We present an abstraction of the genetic algorithm (GA), termed populationbased incremental learning (PBIL), that explicitly maintains the statistics contained in a GA’s population, but which abstracts away the crossover operator and redefines the role of the population. This results in PBIL being ..."
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Cited by 212 (13 self)
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We present an abstraction of the genetic algorithm (GA), termed populationbased incremental learning (PBIL), that explicitly maintains the statistics contained in a GA’s population, but which abstracts away the crossover operator and redefines the role of the population. This results in PBIL being
ROAMing Terrain: Realtime Optimally Adapting Meshes
, 1997
"... Terrain visualization is a difficult problem for applications requiring accurate images of large datasets at high frame rates, such as flight simulation and groundbased aircraft testing using synthetic sensor stimulation. On current graphics hardware, the problem is to maintain dynamic, viewdepend ..."
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Cited by 287 (10 self)
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Terrain visualization is a difficult problem for applications requiring accurate images of large datasets at high frame rates, such as flight simulation and groundbased aircraft testing using synthetic sensor stimulation. On current graphics hardware, the problem is to maintain dynamic, view
A Survey of Evolution Strategies
 Proceedings of the Fourth International Conference on Genetic Algorithms
, 1991
"... Similar to Genetic Algorithms, Evolution Strategies (ESs) are algorithms which imitate the principles of natural evolution as a method to solve parameter optimization problems. The development of Evolution Strategies from the first mutationselection scheme to the refined (¯,)ES including the gen ..."
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Cited by 263 (3 self)
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Similar to Genetic Algorithms, Evolution Strategies (ESs) are algorithms which imitate the principles of natural evolution as a method to solve parameter optimization problems. The development of Evolution Strategies from the first mutationselection scheme to the refined (¯,)ES including
Quality of Service Guarantees in Virtual Circuit Switched Networks
 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
, 1995
"... We review some recent results regarding the problem of providing deterministic quality of service guarantees in slotbased virtual circuit switched networks. The concept of a service curve is used to partially characterize the service that virtual circuit connections receive. We find that service cu ..."
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Cited by 255 (10 self)
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, and we consider scheduling algorithms that can support the allocated service curves. Such an approach provides the required degree of isolation between the connections in order to support performance guarantees, without precluding statistical multiplexing. Finally, we examine the problem of enforcing
A tutorial on crosslayer optimization in wireless networks
 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
, 2006
"... This tutorial paper overviews recent developments in optimization based approaches for resource allocation problems in wireless systems. We begin by overviewing important results in the area of opportunistic (channelaware) scheduling for cellular (singlehop) networks, where easily implementable my ..."
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Cited by 248 (29 self)
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This tutorial paper overviews recent developments in optimization based approaches for resource allocation problems in wireless systems. We begin by overviewing important results in the area of opportunistic (channelaware) scheduling for cellular (singlehop) networks, where easily implementable
Results 11  20
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10,863