An effective hybrid ant lion algorithm to minimize mean tardiness on permutation flow shop scheduling problem

International Journal of Advances in Intelligent Informatics

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Field Value
 
Title An effective hybrid ant lion algorithm to minimize mean tardiness on permutation flow shop scheduling problem
 
Creator Utama, Dana Marsetiya
Widodo, Dian Setiya
Ibrahim, Muhammad Faisal
Dewi, Shanty Kusuma
 
Subject Optimization; Mean tardiness; Hybrid ant lion; Flow shop; Scheduling
 
Description This article aimed to develop an improved Ant Lion algorithm. The objective function was to minimize the mean tardiness on the flow shop scheduling problem with a focus on the permutation flow shop problem (PFSP). The Hybrid Ant Lion Optimization Algorithm (HALO) with local strategy was proposed, and from the total search of the agent, the NEH-EDD algorithm was applied. Moreover, the diversity of the nominee schedule was improved through the use of swap mutation, flip, and slide to determine the best solution in each iteration. Finally, the HALO was compared with some algorithms, while some numerical experiments were used to show the performances of the proposed algorithms. It is important to note that comparative analysis has been previously conducted using the nine variations of the PFSSP problem, and the HALO obtained was compared to other algorithms based on numerical experiments.
 
Publisher Universitas Ahmad Dahlan
 
Contributor
 
Date 2020-03-29
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion

 
Format application/pdf
 
Identifier http://ijain.org/index.php/IJAIN/article/view/385
10.26555/ijain.v6i1.385
 
Source International Journal of Advances in Intelligent Informatics; Vol 6, No 1 (2020): March 2020; 23-35
2548-3161
2442-6571
 
Language eng
 
Relation http://ijain.org/index.php/IJAIN/article/view/385/ijain_v6i1_p23-35
 
Rights https://creativecommons.org/licenses/by-sa/4.0
 

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