A Novel Multi-objective Lion Swarm Intelligent Optimization Based on Cloud Model for Manufacturing Scheduling Problem

Abstract

Abstract With the continuous upgrading of industrial manufacturing, various artificial intelligence technologies have gradually been applied to the field of industrial production, including swarm intelligence optimization algorithms. Aiming at the flow shop scheduling problem (FSP) and job shop scheduling problem (JSP) in industrial production, which are NP-hard problems, we use a multi-objective optimization method to solve them. We proposed a novel multi-objective optimization named multi-objective lion swarm optimization based on cloud model mutation (CMOLSO). This new optimization algorithm, which is based on the Lion Swarm Optimization (LSO), introduces the concept of cloud model and cloud generator algorithm. The introduction of the cloud model mechanism can expand the search range of CMOLSO in high-dimensional multi-objective problems, make it avoid falling into local extremes, and improve its optimization accuracy. Compared with the traditional multi-objective optimization, the new algorithm CMOLSO achieves better performance, and it can effectively solve the scheduling problems in practice.