How to Solve It: Modern Heuristics

Michalewicz, Zbigniew; Fogel, David B.

doi:10.1007/978-3-662-07807-5

Cited by 730 publications

(584 citation statements)

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“…A genetic algorithm (GA) simulates the behaviour of Darwinian natural selection and converges toward an optimal solution through successive generations of recombination, mutation, and selection, as shown in the pseudocode of Figure 2 (adapted from [15]). A potential solution in the problem space is represented as a chromosome.…”

Section: Overviewmentioning

confidence: 99%

Evolving Toward the Perfect Schedule: Co-scheduling Job Assignments and Data Replication in Wide-Area Systems Using a Genetic Algorithm

Phan

Ranganathan²,

Sion

2005

Job Scheduling Strategies for Parallel Processing

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Traditional job schedulers for grid or cluster systems are responsible for assigning incoming jobs to compute nodes in such a way that some evaluative condition is met. Such systems generally take into consideration the availability of compute cycles, queue lengths, and expected job execution times, but they typically do not account directly for data staging and thus miss significant associated opportunities for optimisation. Intuitively, a tighter integration of job scheduling and automated data replication can yield significant advantages due to the potential for optimised, faster access to data and decreased overall execution time. In this paper we consider data placement as a first-class citizen in scheduling and use an optimisation heuristic for generating schedules. We make the following two contributions. First, we identify the necessity for co-scheduling job dispatching and data replication assignments and posit that simultaneously scheduling both is critical for achieving good makespans. Second, we show that deploying a genetic search algorithm to solve the optimal allocation problem has the potential to achieve significant speed-up results versus traditional allocation mechanisms. Through simulation, we show that our algorithm provides on average an approximately 20-45% faster makespan than greedy schedulers.

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Section: Overviewmentioning

confidence: 99%

Evolving Toward the Perfect Schedule: Co-scheduling Job Assignments and Data Replication in Wide-Area Systems Using a Genetic Algorithm

Phan

Ranganathan²,

Sion

2005

Job Scheduling Strategies for Parallel Processing

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show abstract

“…The IDS method of signature string evaluation is analogous to the Boolean Satisfiability Problem (SAT): the enumeration (or exhaustion) of a search space of n variables against a function to determine which variables return true from that function [2]. The SAT defines our formal problem classification to be Nondeterministic Polynomial time (NP)-Hard, preventing it from being solved in polynomial time [3].…”

Section: Problem Motivationmentioning

confidence: 99%

An Artificial Immune System-Inspired Multiobjective Evolutionary Algorithm with Application to the Detection of Distributed Computer Network Intrusions

Haag

Lamont

Williams

et al. 2007

Lecture Notes in Computer Science

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Today's signature-based intrusion detection systems are reactive in nature and storage-limited. Their operation depends upon catching an instance of an intrusion or virus and encoding it into a signature that is stored in its anomaly database, providing a window of vulnerability to computer systems during this time. Further, the maximum size of an Internet Protocol-based message requires the database to be huge in order to maintain possible signature combinations. In order to tighten this response cycle within storage constraints, this paper presents an innovative Artificial Immune System-inspired Multiobjective Evolutionary Algorithm. This distributed intrusion detection system (IDS) is intended to measure the vector of tradeoff solutions among detectors with regard to two independent objectives: best classification fitness and optimal hypervolume size. Our antibody detectors promiscuously monitor network traffic for exact and variant abnormal system events based on only the detector's own data structure and the application domain truth set, responding heuristically. Applied to the MIT-DARPA 1999 insider intrusion detection data set, our software engineered algorithm correctly classifies normal and abnormal events at a high level which is directly attributed to a detector affinity threshold.

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“…Even though these methods provide no formal guarantee for global optimization, they are reliable strategies and offer a reasonable computational effort in the optimization of multivariable functions (Michalewicz and Fogel, 1999). In fact, some papers have reported the application of SA and GA in parameter estimation using chemical engineering models (Kleiber and Axmann, 1998;Park and Froment, 1998;Costa et al, 2000).…”

Section: Introductionmentioning

confidence: 99%

The performance of simulated annealing in parameter estimation for vapor-liquid equilibrium modeling

Bonilla-Petriciolet

Bravo-Sánchez

Castillo-Borja

et al. 2007

Braz. J. Chem. Eng.

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-In this paper we report the application and evaluation of the simulated annealing (SA) optimization method in parameter estimation for vapor-liquid equilibrium (VLE) modeling. We tested this optimization method using the classical least squares and error-in-variable approaches. The reliability and efficiency of the data-fitting procedure are also considered using different values for algorithm parameters of the SA method. Our results indicate that this method, when properly implemented, is a robust procedure for nonlinear parameter estimation in thermodynamic models. However, in difficult problems it still can converge to local optimums of the objective function.

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How to Solve It: Modern Heuristics

Cited by 730 publications

References 0 publications

Evolving Toward the Perfect Schedule: Co-scheduling Job Assignments and Data Replication in Wide-Area Systems Using a Genetic Algorithm

Evolving Toward the Perfect Schedule: Co-scheduling Job Assignments and Data Replication in Wide-Area Systems Using a Genetic Algorithm

An Artificial Immune System-Inspired Multiobjective Evolutionary Algorithm with Application to the Detection of Distributed Computer Network Intrusions

The performance of simulated annealing in parameter estimation for vapor-liquid equilibrium modeling

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