Memetic algorithms applied to the optimization of workflow compositions

Ludwig, Simone A.

doi:10.1016/j.swevo.2012.12.001

Cited by 9 publications

(6 citation statements)

References 29 publications

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“…The work considered various QoS attributes in fitness function such as service response time, service cost, service reliability and service availability and compositions (antibodies) with best fitness are considered as candidate solution for the composition in the algorithm. Ludwig et al [13] applied memetic algorithm as an improved approach by combined use of swarm intelligence algorithm or any other evolutionary method with a local search technique, to achieve better results. The work used the algorithm called Munkres as local search technique combined with GA as well as a PSO approach as a memetic algorithm.…”

Section: Related Workmentioning

confidence: 99%

A Multi-Objective Optimization of Cloud Based SLA-Violation Prediction and Adaptation

Gaur¹,

Dhyani²,

Rishi³

2016

IJITCS

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Abstract-Monitoring of Cloud services is vital for both service providing organizations and consumers. The service providers need to maintain the quality of service to comply their services with the QoS parameters defined in SLA's such as response time, throughput, delay through continuous monitoring of services. The dynamic monitoring involves prediction of SLA violations and subsequent adaptation of the service compositions. The task of adaptation is in fact the task of discovering another plausible composition in the face of services recorded to have generated QoS violations. QoS-Driven Utility based service composition approach considers the individual user's priorities for QoS parameters and determines the overall utility measure of the service composition for the end user. In this work we present the problem of service composition adaptation as a multiobjective assignment optimization problem, which in turn is a NP-hard problem. The evolutionary algorithm GA with Tabu has been formulated as a Memetic and Pareto optimal approach for the adaptation problem and analyzed for efficiency in solving the problem.Index Terms-Quality of service, service level agreement, service composition, service utility.

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Section: Related Workmentioning

confidence: 99%

A Multi-Objective Optimization of Cloud Based SLA-Violation Prediction and Adaptation

Gaur¹,

Dhyani²,

Rishi³

2016

IJITCS

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“…In recent years, the Memetic Algorithm (MA) gradually becomes a research hotspot in evolutionary computing and achieves good effect in many applications [17][18][19][20]. In the standard flowchart of MA, a local search (LS) strategy is executed after crossover and mutation operations.…”

Section: Optimization By the Memetic Algorithmmentioning

confidence: 99%

An Initial Value Calibration Method for the Wheel Force Transducer Based on Memetic Optimization Framework

Lin

Zhang

Yang

et al. 2013

Mathematical Problems in Engineering

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Some initial values of the wheel force transducer (WFT) change after being mounted in the vehicle. The traditional static calibration is inadequate to fully obtain these initial values. Aiming to this problem, an online initial value calibration method is proposed. The method does not require any additional calibration equipment or manual operation and just requires the vehicle mounted with the WFT to be driven on a flat road with constant speed. In this way, an initial value mode is constructed and then converted to an optimization problem. To solve this problem and acquire the right initial value, an improved Memetic framework based on particle swarm optimization (PSO) and Levenberg-Marquardt (LM) is adopted. To verify the effect of the proposed method, the real WFT data is used and the comparative test is carried out. The experiment result shows that the proposed method is superior to the traditional one and can improve the measurement accuracy effectively.

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“…Aforementioned algorithms are widely applied by researchers in many different areas [48][49][50][51]. However, there is no particular algorithm to gain the most appropriate solution for all optimization problems.…”

Section: Introductionmentioning

confidence: 99%

Lion Optimization Algorithm (LOA): A nature-inspired metaheuristic algorithm

Yazdani

Jolai

2015

Journal of Computational Design and Engineering

389

159

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During the past decade, solving complex optimization problems with metaheuristic algorithms has received considerable attention among practitioners and researchers. Hence, many metaheuristic algorithms have been developed over the last years. Many of these algorithms are inspired by various phenomena of nature. In this paper, a new population based algorithm, the Lion Optimization Algorithm (LOA), is introduced. Special lifestyle of lions and their cooperation characteristics has been the basic motivation for development of this optimization algorithm. Some benchmark problems are selected from the literature, and the solution of the proposed algorithm has been compared with those of some well-known and newest meta-heuristics for these problems. The obtained results confirm the high performance of the proposed algorithm in comparison to the other algorithms used in this paper.

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Memetic algorithms applied to the optimization of workflow compositions

Cited by 9 publications

References 29 publications

A Multi-Objective Optimization of Cloud Based SLA-Violation Prediction and Adaptation

A Multi-Objective Optimization of Cloud Based SLA-Violation Prediction and Adaptation

An Initial Value Calibration Method for the Wheel Force Transducer Based on Memetic Optimization Framework

Lion Optimization Algorithm (LOA): A nature-inspired metaheuristic algorithm

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