Research On The Joint Optimization Problem Of Seru Production Based On Multi-skilled Worker Assignment

With the rapid development of manufacturing technology,the current market environment is characterized by short product life cycles,uncertain product types and unstable demand.Traditional production methods are difficult to cope with changing market demands,and companies need to seek a new production method to cope with the market environment.Seru production is a production method that combines flexibility and efficiency.Seru production system includes two key decisions : Seru formation and Seru scheduling.With only one of them optimized,the global optimal solution cann’t be obtained.The multi-skilled worker assignment affects the productivity of the Seru production system.Therefore,this thesis considers the heterogeneity of multi-skilled workers,and studies the joint optimization problem of Seru production with the optimization goals of minimizing makespan and minimizing the total labor cost.The main research work of this thesis is as follows:(1)Taking the divisional Seru production under non-almighty workers as the research object,and the skill sets of workers are taken as known conditions.Considering the heterogeneity of multi-skilled workers,mainly including the difference in the skill mix of workers and the difference in the skill proficiency level of workers,make joint decisions on the two key decisions of Seru formation and Seru scheduling.A mathematical model for joint optimization of Seru production with multi-skilled workers assignment is established.The optimization goal is to minimize makespan and minimize the total labor cost.(2)For the problem proposed in this thesis,the multi-objective problem is transformed into a single-objective problem by using linear weighting.For small-scale problems,a two-stage algorithm is designed.In the first stage,the problem of Seru formation is solved,and the optimal Seru structure is obtained by enumeration of feasible solutions.The second stage is to solve the Seru scheduling problem on the basis of the first stage,using the backtracking algorithm and CPLEX to solve the optimal Seru scheduling under the given Seru formation.(3)For large-scale problems,a cooperative coevolution algorithm is designed,and the Seru formation population and Seru scheduling population are associated by using the idea of co-evolutionary,that is,by introducing a better individual in a subpopulation as a collaborator to help another population complete the evolution,the co-evolution of Seru formation and Seru scheduling population is realized.Finally,the optimal solution of joint optimization is obtained.(4)The algorithm is realized by C ++.Experiments are designed to compare the results obtained by the two-stage algorithm with those obtained by the cooperative coevolution algorithm for different data sizes.The experimental results show that the two-stage algorithm is superior to the cooperative coevolution algorithm for solving small-scale problems.The cooperative coevolution algorithm for large-scale problems has better performance than the two-stage algorithm.