Jan 1, 2010 · In this paper, we propose two hybrid genetic algorithms which we designate as the Critical Path Genetic Algorithm (CPGA) and the Task Duplication Genetic Algorithm (TDGA). Our developed algorithms show the effect of the amalgamation of greedy algorithms with the genetic algorithm meta-heuristic.

This study proposes an evolutionary based scheduling algorithm called Genetic Algorithm for Task Scheduling in parallel and distributed computing environment (GeneTaS) to schedule a group of tasks on the available resources.

The paper defines a general model for a DHOS and a DHES and presents a genetic algorithm (GA) to solve the task scheduling problem in the defined DCS. The performance of the proposed GA is compared with the list scheduling algorithm in a DHOS and with the one-level reach-out greedy algorithm (OLROG) in a DHES.

Sep 12, 2021 · It presents an adaptive scheduling approach, ‘Dynamic Genetic Algorithm for Earliest Completion Time (dGA-ECT)’, with the objective of reducing schedule length by efficient utilization of distributed resources. The algorithm improves the throughput of a multi-workflow distributed computing platform.

May 1, 2017 · Efficient genetic algorithm for task scheduling (EGA-TS) that is presenting in this paper tackles these issues via creating a new initial population function and adding improved operators to the basic genetic algorithm.

Jan 1, 2010 · The scheduling and mapping of the precedence-constrained task graph to processors is considered to be the most crucial NP-complete problem in parallel and distributed computing systems. Several genetic algorithms have been developed to solve this problem.

Aug 28, 2024 · A heuristic-based TDCC (Time, distance, cost and computing-power) algorithm is proposed to optimize the task scheduling problem in this heterogeneous system for genetic algorithm-based “cloud-fog” computing, including execution time, operational cost, distance and total computing power resources.

Few scheduling algorithms are proposed for Heterogeneous Distributed Computing Systems (HeDCSs). In this paper, we present a new approach which uses a customized genetic algorithm to produce high-quality tasks schedules for HeDCSs.

Sep 12, 2021 · It presents an adaptive scheduling approach, ‘Dynamic Genetic Algorithm for Earliest Completion Time (dGA-ECT)’, with the objective of reducing schedule length by efficient utilization of...

This paper offers a new strategy for task scheduling which is based on genetic algorithm. The final results show that proposed algorithm is an improvisation over Standard Genetic Algorithm in terms of makespan and resource utilization. Keywords – Distributed Scheduling, Genetic Algorithm, Meta- Heuristic, Makespan. I. INTRODUCTION