Research On Flexible Job Shop Scheduling Problem With Automated Guided Vehicle

With the development of manufacturing automation technology and the improvement of labor costs,the phenomenon of introducing automated guided vehicles(AGVs)into manufacturing units is relatively common.In order to achieve rapid response and deliver as soon as possible,enterprises need establish a reasonable production model which using excellent optimization algorithm.In the traditional flexible work shop model,the moving time of the AGVs was ignored.However,these times are objective and account for a considerable proportion of the total processing time.In recent years,the scheduling problem which consider of handling time has drawn more and more attention from researchers.In order to get the AGV optimal scheduling scheme to minimize the processing time and get the optimal number of AGVs,this paper established a flexible shop scheduling model with AGV handling.Aiming at the characteristics of the model,a new particle swarm optimization algorithm based on handling procedure,machine tool and AGV distribution was proposed.The new particle swarm optimization algorithm adopted a new position update method,which was based on the idea of genetic algorithm.Numerical examples can demonstrate the effectiveness and feasibility of the improved particle swarm optimization.Besides,it was found that AGV conforms to the boundary decreasing effect.That is,as the number of AGVs increases,the total processing time decreases,but the time for each AGV shortening decreases.Based on the flexible Job Shop scheduling model with AGV,this paper proposes an advanced whale algorithm,which combined with chaotic local search to solve the problem of AGV flexible shop scheduling with learning-deteriorating effects.Numerical examples can demonstrate the effectiveness and feasibility of the proposed algorithm.It was found that the effect of different effect factors on processing time is different.This paper also found that the processing time of considering learning effect,or considering deteriorating effect,or considering learning-deteriorating effect,or considering no effect was different.And it was found that the effect of different batches and AGVs on the processing time was different.In the AGV optimal human-machine replacement ratio problem in flexible shop,this paper established a flexible shop scheduling model that is jointly handled by employees and AGVs,and aimed at minimum completion time and minimum cost.According to the characteristics of the model,heuristic rule allocation AGV and staff handling were proposed.Through the example,we got the optimal AGV replacement ratio,and found that the AGV optimal replacement ratio was related to the price of AGV.