The Hybrid Ant Lion Optimization Flow Shop Scheduling Problem for Minimizing Completion Time

Abstract

This article aims to develop the Ant Lion Optimization (ALO) algorithm for the Permutation Flow Shop Scheduling Problem (PFSP). We use the objective function to minimize completion time. We propose the Hybrid Ant Lion Optimization (HALO) algorithm to minimize completion time in PFSP. We offer one of the total search agents on HALO using the NEH algorithm. Determination of the position of the search agent using a Large Rating Value (LRV). How it works from LRV is sorting from the largest value to the value. To improve the solution for each iteration, we also use swap, flip, and slide exchange procedures. The performance of the HALO algorithm is measured by Efficiency Index Perscentage (EIP). HALO algorithm will be compared with several other algorithms, namely ALO algorithm and Hybrid Whale Optimization Algorithm (HWOA). We conducted numerical experiments with Ten variations of experimental data are used to show the performance of the HALO algorithm. Based on numerical experiments, the HALO algorithm is useful for minimizing completion time.