Competitive swarm optimizer for Solving Flexible Jobshop Scheduling Problem

F1exible job shop scheduling problem (FJSP) is an extension of job shop scheduling problem (JSP) that has received increasing attention in recent decades. FJSP is a high-dimensional combinatorial optimization problem. Using accurate algorithms to solve them is a challenge and costly. The difference is that a meta-heuristic algorithm is an algorithm based on intuition or experience that gives a feasible solution to the problem at an acceptable cost (referring to calculation time and space). Particle Swarm optimization (PSO) is a classic meta-heuristic algorithm that has achieved many successful applications. However, it is easy to converge prematurely when solving high-dimensional problems. Competitive Swarm optimizer (CSO), as a variant of particle swarm optimization, has excellent global search capabilities to deal with high-dimensional problems. Therefore, this article uses CSO to solve FJSP. We introduced five other algorithms as a comparison to verify our algorithm. Numerical comparison results show that CSO can optimize all FJSP better overall.

I. Introduction

Under the continuous promotion of the digital economy, the production characteristics of the manufacturing industry have also undergone tremendous changes [1], [2]. The original single-type, large-scale rigid production has gradually changed to a multi-type, small-batch flexible production, and the profitability of a single functional product has been changed [3]. The transformation of the model to a comprehensive profit model combining services and products further complicates the production process and makes the production process more difficult to control [4]. Therefore, better product quality, higher production efficiency and more advanced production technology have become the key to the competitiveness of manufacturing enterprises [5]. Workshop scheduling is an important part of the production process. A reasonable scheduling plan can effectively improve production efficiency and reduce unnecessary resource loss in the production process, and meet the needs of enterprises to reduce costs and improve product quality [6]. At present, the production scheduling of most manufacturing companies is to use the scheduling plan obtained under ideal conditions, and then rely on manual adjustment to ensure the stability of product production [7]. This makes it difficult to control the labor cost of the company, and the production efficiency is also It is difficult to be promoted. Therefore, with the popularization of flexible production models, how to manage and control complex production processes and achieve high-efficiency workshop scheduling has become one of the focuses of domestic and foreign scholars and enterprises [8].