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

Dana Marsetiya Utama (Departement of Industrial Engineering, University Of Muhammadiyah Malang (UMM))
Dian Setiya Widodo (University of 17 Agustus 1945 Surabaya)
Muhammad Faisal Ibrahim (Universitas Internasional Semen Indonesia)
Shanty Kusuma Dewi (Departement of Industrial Engineering, University Of Muhammadiyah Malang (UMM))

International Journal of Advances in Intelligent Informatics
Vol 6, No 1 (2020): March 2020

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.