Research On Efficient And Energy Saving Of Permutation Flow Shop Scheduling Problem

With the deepening of economic globalization,energy has become a key factor to promote social progress.In China,the energy consumption of manufacturing industry accounts for about 60% of the total energy consumption.How to reduce the energy consumption of manufacturing workshop and improve the production efficiency has attracted more and more attention of manufacturing enterprises.Compared with the transformation of production process and replacement of energy-saving equipment,scientific and reasonable workshop scheduling can achieve the goal of energy saving and emission reduction with less cost,which has become one of the effective methods to solve this problem.In this paper,aiming at the widely existing Permutation Flow Shops Scheduling Problem(PFSP)in discrete manufacturing workshop,the single target maximum completion time,single target energy consumption,multi-target energy consumption and dynamic problems are studied by improving Jaya algorithm,which provides technical support for energy saving and emission reduction of discrete manufacturing system.Firstly,the PFSP is described and a mathematical model is established.An improved Jaya algorithm is proposed to solve the PFSP with the makespan criterion.In the improved Jaya algorithm,four individual updating schemes based on the best and the worst individuals are proposed.Local search for individuals is carried out through four neighborhood structures.Diversity control strategy is adopted to ensure the diversity of population.Finally,the improved Jaya algorithm was used to test 8 sets of Car benchmark instances,21 sets of Rec benchmark instances and 110 sets of Taillard benchmark instances,and the effectiveness of the proposed algorithm was verified by comparison with other algorithms.Secondly,the PFSP is studied to minimize the total energy consumption of the workshop.A mixed integer linear programming model is developed to minimize the total energy consumption of the workshop.An improved multi-objective Jaya algorithm is designed to solve the PFSP with the goal of minimizing the total energy consumption and the makespan.Four kinds of individual updating methods based on the optimal individual and the worst individual are proposed,which include deleting first and then inserting,retaining first and thencompleting etc.In order to further enhance the optimization ability of the algorithm,a variable neighborhood search algorithm based on three neighborhood structures is designed to perform variable neighborhood search on some individuals including the contemporary optimal individuals.The validity of the proposed model and algorithm is verified by testing 29 benchmark instances and comparing with other algorithms.Then,the dynamic event,purpose and mechanism of dynamic multi-objective scheduling problem are described.In order to minimize the makespan,the total energy consumption of the workshop and the deviation degree of the process,the dynamic scheduling problem of the adapted Car instance and Taillard instance is solved.The results show that the proposed algorithm has strong adaptability in the dynamic scheduling problem of the PFSP.Finally,the research of this paper is summarized and the future research is prospected.