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ZENODO
Article . 2010
License: CC BY
Data sources: Datacite
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ZENODO
Article . 2010
License: CC BY
Data sources: ZENODO
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ZENODO
Article . 2010
License: CC BY
Data sources: Datacite
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Comparison Of Three Meta Heuristics To Optimize Hybrid Flow Shop Scheduling Problem With Parallel Machines

descriptionPublicationkeyboard_double_arrow_right Article 20 Feb 2010 English Publisher:Zenodo
Authors: Wahyudin P. Syam; Al-Harkan, Ibrahim M.;

doi: 10.5281/zenodo.1328906 , 10.5281/zenodo.1328905

Comparison Of Three Meta Heuristics To Optimize Hybrid Flow Shop Scheduling Problem With Parallel Machines

Abstract

This study compares three meta heuristics to minimize makespan (Cmax) for Hybrid Flow Shop (HFS) Scheduling Problem with Parallel Machines. This problem is known to be NP-Hard. This study proposes three algorithms among improvement heuristic searches which are: Genetic Algorithm (GA), Simulated Annealing (SA), and Tabu Search (TS). SA and TS are known as deterministic improvement heuristic search. GA is known as stochastic improvement heuristic search. A comprehensive comparison from these three improvement heuristic searches is presented. The results for the experiments conducted show that TS is effective and efficient to solve HFS scheduling problems.

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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