Scheduling algorithm for real-time tasks using multiobjective hybrid genetic algorithm in heterogeneous multiprocessors system

Yoo, Myungryun; Gen, Mitsuo

doi:10.1016/j.cor.2005.11.016

Cited by 46 publications

(35 citation statements)

References 14 publications

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“…However, using biomass to provide power has a long history in China. China has four sources of biomass resources: 1) Agricultural residues; 2) forestry residues; 3) feces from animal husbandry; 4) industrial waste water and solid waste (Yoo and Gen, 2007).…”

Section: Introduction Current Situation Of Biomass Power Developmentmentioning

confidence: 99%

Vehicle Scheduling Optimization of Biomass Supply Logistics: A Case of Power Plant Supply Chains

Zhang

et al. 2012

Cictp 2012

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The demands and features of biomass power plant have been investigated and analyzed by several researchers. However, the procedures and information flows of supply logistics in biomass power plants still require analysis. In this paper, we put forward a multi-objective model for vehicle scheduling, which is used in biomass power plant supply chains. In addition, a related algorithm for use in uncertain environments is provided. An efficiency plan with the lowest calculated transportation costs will be proposed.

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Section: Introduction Current Situation Of Biomass Power Developmentmentioning

confidence: 99%

Vehicle Scheduling Optimization of Biomass Supply Logistics: A Case of Power Plant Supply Chains

Zhang

et al. 2012

Cictp 2012

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“…However, the important point in the problem we face is that task scheduling is a real-time operation and requires high speed on a grand scale that is, when hundred of task enter the system, it must possess the ability to perform the scheduling operation at the highest possible speed and have close to optimal performance. Different studies have been carried out on task scheduling by using various algorithms such as GA, Fuzzy, PSO [3][4][5][6][7][8], or a combination of these algorithms.…”

Section: Introductionmentioning

confidence: 99%

Prune PSO: A new task scheduling algorithm in multiprocessors systems

HaghNazar¹,

Rahmani²

2010

2010 International Conference on Networking and Information Technology

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the mapping of tasks among processors, which is known as task scheduling is one of the most important issues in multi-processor system. Although various solutions have been proposed, the most optimum method has not been found yet.Therefore, some expert in this field have tried developmental algorithms such as PSO and genetic. In this article, we try to study this problem by using the PSO algorithm. However, since this is an MPHard problem and the above mentioned algorithms are of high time complexity, we have tried to increase the speed of obtaining answers, without any resultant decrease in efficiency, through making changes in the PSO algorithm. Results presented in the experimental result of this article show that the speed of convergence increases as compared to the standard PSO.

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“…Implementation has been carried out on different PSO algorithm with Simulated Annealing. Different experiments have been performed on the benchmark problems and shows that the proposed hybrid method was effective and efficient in finding near optimal solutions.Yooet al [14] proposed a multi-objective hybrid genetic algorithm (MOHGA) for real-time tasks on heterogeneous multiprocessor environment with the purpose of minimizing the total tardiness and completion time simultaneously. The adaptive weight approach has been used for multiple objectives.…”

Section: Related Workmentioning

confidence: 99%

Hybrid Genetic Algorithm for Bi-Criteria Multiprocessor Task Scheduling with Communication Delay

Dhingra¹,

Dhingra²,

Gupta³

et al. 2016

ACII

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Present work considers the minimization of the bi-criteria function including weighted sum of makespan and total completion time for a Multiprocessor task scheduling problem.Genetic algorithm is the most Keywords:Multiprocessor task scheduling, heuristics, Hybrid Genetic algorithm, makespan, Total Completion time. 1.INTRODUCTIONParallel processing is the most promising approach for meeting the increased computational requirements thathas introduced a number of problems including multiprocessor task scheduling. Usually a large program is divided into smaller tasks havingsome dependencies representing the precedence constraints such that a task cannot be started until all its predecessors have finished. The goal of a task scheduling algorithm is to schedule all the tasks on the given number of available processors without violating precedence constraints so as to minimize the different performance measures in order to maximize the throughput and utilization of the system. The multiprocessor task scheduling problem with precedence constraints belongs to the class of NP hard problems and its importance led to several comparative studies. The conventional research on scheduling considers heuristic based algorithms which are divided into three categories: list scheduling, clustering based and duplication based. Among heuristic algorithms, List scheduling algorithms are commonly used and work by assigning priority to each task according to attributes such as t-level (top level), b-level (bottom level), static level (sl) and ALAP (As Late As Possible)

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Scheduling algorithm for real-time tasks using multiobjective hybrid genetic algorithm in heterogeneous multiprocessors system

Cited by 46 publications

References 14 publications

Vehicle Scheduling Optimization of Biomass Supply Logistics: A Case of Power Plant Supply Chains

Vehicle Scheduling Optimization of Biomass Supply Logistics: A Case of Power Plant Supply Chains

Prune PSO: A new task scheduling algorithm in multiprocessors systems

Hybrid Genetic Algorithm for Bi-Criteria Multiprocessor Task Scheduling with Communication Delay

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