Research On Application Of Grey Wolf Algorithm In Typical Shop Scheduling Problem

Production scheduling is one of the important tasks in production management of manufacturing enterprises.Among them,the parallel machine shop scheduling problem(PMSP)and the permutation flow shop scheduling problem(PFSP)are two typical types of shop scheduling problems.They are simplified models of many actual production system scheduling problems for n workpieces on m machines The wherein the former is characterized in that each of the n workpieces can be processed on any of the m machines,and the latter is characterized in that the n workpieces are processed in the same order via the m machines.It has been proved that the two types of typical shop scheduling problems of three or more machines are NP problems,and it is also a hot issue in the current production scheduling research.In recent years,with the rapid development of computer technology and artificial intelligence,the intelligent algorithm of production scheduling has been paid more and more attention.Grey Wolf algorithm is a newly proposed intelligent optimization algorithm,because of its effectiveness and efficiency,has been applied to solve a variety of difficult combination optimization problem.In this paper,we use the Grey Wolf algorithm to study the above two typical shop scheduling problems.Firstly,with the maximum completion time as the optimization target,a Grey Wolf algorithm is designed for the unrelated parallel machine scheduling problem and the permutation flow shop scheduling problem.The initial population is generated randomly according to the coding method based on procedure order,and the efficient update operator is used to 30 randomly generated examples and 240 standard test cases were tested,and the test results were compared with the genetic algorithm.The experimental results show the feasibility and effectiveness of the Grey Wolf algorithm.Secondly,based on the maximum completion time and the total process time as the optimization target,a multi-objective Grey Wolf algorithm is designed for multi-objective permutation flow shop scheduling problem based on the procedure order coding method.The heuristic algorithm NEH and the random generation are used to generate the initial population.The results are compared with the classical multi-objective algorithm—SPEA2 algorithm.The test results show the superiority of the multi-objective Grey Wolf algorithm.Compared with the Backtracking Search algorithm,the optimal solution is accelerated by 430s,which reduces the total completion time by 9.75%,which further validates the superiority of the Grey Wolf algorithm.