Whale Optimization Algorithms for Multi-Objective Flowshop Scheduling Problems

Abstract

One of the most common scheduling classes in the industry is Flow Shop Scheduling Problem(FSP). Given a set of jobs that must be completed in a series of identical stages, each stage is performed by asingle machine. The goal of the FSP is to find a series of jobs that meets specific optimization criteria. Multiobjective FSP (MOFSP) is an FSP with more than one optimization target. This study investigates the MOFSPsolution using two variants of the Whale Optimization Algorithm technique, namely the basic WhaleOptimization Algorithm (WOA) and an improved Whale Optimization Algorithm (I-WOA). The objectivecriteria are makespan and total flow time. This study aims to examine the performance of WOA and I-WOA anddetermine how the weight ratio of optimization criteria affects each method. Several experiments wereconducted using the Taillard Benchmark, and it was concluded that in general, WOA outperforms I-WOA, andthe best weight ratio is makespan:total flow time is 75:25.