JOB-SHOP SCHEDULING PROBLEM BASED ON IMPROVED CUCKOO SEARCH ALGORITHM

This paper makes an in-depth exploration into the job-shop scheduling problem (JSP). After reviewing the related literature, the local search mechanism of the particle swarm algorithm (PSA) and the largespan search principle of standard cuckoo search algorithm (CSA) were combined into an improved cuckoo search algorithm (ICSA), which is capable of both local search and global search. Later, several simulation experiments were carried out on the LA type typical library proposed by Lawrence, and the stability and accuracy of the ICSA was contrasted with those of the PSA and the genetic algorithm (GA) based on the means and variances in multiple iterations. After the comparison, a convergence analysis of the ICSA was specially designed for our model. The results demonstrate that the ICSA provides a better tool for solving the JSP than other algorithms. The research findings lay a solid theoretical basis for the JSP in the actual production process.