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 a single 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 MOFSP solution using two variants of the Whale Optimization Algorithm technique, namely the basic Whale Optimization Algorithm (WOA) and an improved Whale Optimization Algorithm (I-WOA). The objective criteria are makespan and total flow time. This study aims to examine the performance of WOA and I-WOA and determine how the weight ratio of optimization criteria affects each method. Several experiments were conducted using the Taillard Benchmark, and it was concluded that in general, WOA outperforms I-WOA, and the best weight ratio is makespan:total flow time is 75:25.

Keywords

• Scheduling
• Flow shop
• Multi-objective FSP
• Whale optimization algorithm