Flexible Job Shop Scheduling Based On Improved Harmony Search Algorithm

The development of China’s manufacturing industry has become a key strategic goal of the industrial power.Workshop production scheduling is the core link of the development of manufacturing industry,which shows that workshop production scheduling plays a key role in the development of a country.Compared with the traditional job shop scheduling,flexible job shop scheduling is more flexible and close to the actual production situation.However,it is also more complex and more difficult to solve,which belongs to a typical NP-hard problem.Therefore,researchers in various fields began to study more effective methods to solve flexible job shop scheduling on a large scale.Harmony search algorithm is simple in structure and easy to operate.It has strong search ability and is suitable for complex combinatorial optimization problems.In this paper,an improved harmony search algorithm is used to solve the flexible job shop scheduling problem,and the research and discussion are carried out with the minimum completion time as the optimization goal.First of all,based on the characteristics of the flexible job shop scheduling problem,a mathematical model is established,and a discrete improved harmony search algorithm is proposed for solution.The improvement mainly includes the following aspects.First,the harmony search algorithm that mainly solves continuous problems is combined with the discretization of the characteristics of the problem to solve the problem.At the same time,the two-stage combined coding strategy based on the process is used to encode.Moreover,for the initial solution problem,a global random mixed initialization method is adopted to ensure the quality and diversity of the initial solution.Next,in order to accelerate convergence,a group evolution method of creating multiple harmony is used in the search process of the algorithm,and the resources accumulated in the harmony memory bank are fully utilized to improve the convergence speed.At last,to further improve search performance,an intelligent mutation operator is introduced in the search process to achieve balanced machine load distribution and increase the probability of finding the optimal solution.Secondly,after designing and solving the steps of the improved harmony search algorithm,analyze the algorithm’s parameter characteristics,and use the orthogonal test method to optimize its important parameters;After verifying the performance of the improved harmony search algorithm,the improved harmony search algorithm with the optimal parameter configuration is applied to solve the benchmark case,and compared with the test results of similar algorithms and other algorithms,the accuracy of the improved harmony search algorithm for flexible job shop scheduling is proved.Finally,in order to further verify the feasibility of the improved harmony search algorithm,the improved harmony search algorithm is applied to the actual production shop case,then compared with the results of other different algorithms,which shows that the algorithm not only improves the accuracy of solving flexible job shop scheduling,but also has high feasibility and practicability.