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Flow shop scheduling with WWO

Sumit Mathur, Mabel Brijet Johnson

Abstract


This paper focuses on reviewing the method used to solve the problem of flow shop scheduling using one of the efficient nature inspired algorithm that is water wave optimization. It has been proven to be one of the most efficient method of optimization in every field and us widely used nowadays because of its methodologies and efficiency. The Water Wave Optimization can be used for various different types of flow shop scheduling. The paper focuses on solutions of no-wait flow shop scheduling, permutation flow shop scheduling and hybrid flow shop scheduling problems by making modifications in the water wave optimization and the satisfactory results. In this analysis,  Nature  impressed  algorithms  are  projected  to  unravel  the three sorts of issues are permutation flow search programming issues, permutation flow search programming with setup time issues and permutation flow search programming  with setup time and date issues. The results have been found to be satisfactory and efficient.


Keywords


WWO, NFSP, SWWO, flow, algorithms

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References


Energy-conscious Scheduling Problem in a Flexible Job Shop Using a Discrete Water Wave Optimization Algorithm” by Yi Lu, Jiacheng Lu, Tianhua Jiang(2019)

“An Improved Water Wave Optimization Algorithm with the single wave mechanism for the no-wait flow- shop scheduling problem” by Fuqing Zhao, Lixin Zhang, Huan Liu, Yi Zhang, Weimin Ma, Chuck Zhang & Houbit1Song

“A novel water Optimization based memetic algorithm for flow-shop scheduling “by Xin Yun, Xiaoyi Feng, Xin Lyu, Shouyang Wang, Bo Liu (2016)

An Efficient Methodology for Scheduling Hybrid Flow Shop using Water Wave Optimization Technique” Raviteja Buddala,S.S. Mahaptra, T. Eswara Rao(2016)

“Water wave Optimization: A new nature-inspired metaheuristic” by Yu-Jun Zheng (2015)

A genetic algorithm for flow-shop sequencing Computers & Operations Research, 1995

Scheduling flow shops using differential evolution algorithm European Journal of Operational Research, 2006

A discrete version of particle swarm optimization for flow-shop scheduling problems Computers & Operations Research, 2007


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