Journal ArticleDOI
Genetic algorithms for task scheduling problem
Fatma A. Omara,Mona M. Arafa +1 more
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TLDR
Two genetic algorithms are developed with some heuristic principles that have been added to improve the performance and it has been found that the developed algorithms always outperform the traditional algorithms.About:
This article is published in Journal of Parallel and Distributed Computing.The article was published on 2010-01-01. It has received 194 citations till now. The article focuses on the topics: Quality control and genetic algorithms & Genetic representation.read more
Citations
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Journal ArticleDOI
A heuristic-based hybrid genetic-variable neighborhood search algorithm for task scheduling in heterogeneous multiprocessor system
Yun Wen,Hua Xu,Jiadong Yang +2 more
TL;DR: A heuristic-based hybrid genetic-variable neighborhood search algorithm is proposed for the minimization of makespan in the heterogeneous multiprocessor scheduling problem, and significantly outperforms several related algorithms in terms of the schedule quality.
Journal ArticleDOI
Resource provisioning and work flow scheduling in clouds using augmented Shuffled Frog Leaping Algorithm
Parmeet Kaur,Shikha Mehta +1 more
TL;DR: An augmented Shuffled Frog Leaping Algorithm (ASFLA) based technique for resource provisioning and workflow scheduling in the Infrastructure as a service (IaaS) cloud environment is presented and outperforms Particle Swarm Optimization and SFLA.
Journal ArticleDOI
Task scheduling for cloud computing using multi-objective hybrid bacteria foraging algorithm
TL;DR: This paper explores the task scheduling algorithm using a hybrid approach, which combines desirable characteristics of two of the most widely used biologically-inspired heuristic algorithms, the genetic algorithms and the bacterial foraging algorithms in the computing cloud.
Journal ArticleDOI
An enhanced genetic algorithm with new operators for task scheduling in heterogeneous computing systems
TL;DR: A genetic-based algorithm as a meta-heuristic method to address static task scheduling for processors in heterogeneous computing systems and improves the performance of genetic algorithm through significant changes in its genetic functions and introduction of new operators that guarantee sample variety and consistent coverage of the whole space.
Journal ArticleDOI
HSGA: a hybrid heuristic algorithm for workflow scheduling in cloud systems
TL;DR: A hybrid heuristic method (HSGA) is proposed to find a suitable scheduling for workflow graph, based on genetic algorithm in order to obtain the response quickly moreover optimizes makespan, load balancing on resources and speedup ratio.
References
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Book
Adaptation in natural and artificial systems
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Book
Introduction to Algorithms
TL;DR: The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures and presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers.
Journal ArticleDOI
Adaptive probabilities of crossover and mutation in genetic algorithms
M. Srinivas,Lalit M. Patnaik +1 more
TL;DR: An efficient approach for multimodal function optimization using genetic algorithms (GAs) and the use of adaptive probabilities of crossover and mutation to realize the twin goals of maintaining diversity in the population and sustaining the, convergence capacity of the GA are described.
Journal ArticleDOI
Evolutionary computation: comments on the history and current state
TL;DR: The purpose, the general structure, and the working principles of different approaches, including genetic algorithms (GA), evolution strategies (ES), and evolutionary programming (EP) are described by analysis and comparison of their most important constituents (i.e. representations, variation operators, reproduction, and selection mechanism).
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Static scheduling algorithms for allocating directed task graphs to multiprocessors
Yu-Kwong Kwok,Ishfaq Ahmad +1 more