Research On Multi-skilled Worker Resource-constrained Scheduling Problem In Seru Production System

Seru seisanis a new production mode proposed by Japanese enterprises to better adapt to the market environment with high product variety and low production volume.Seru is widely used in Japanese electronic enterprises with both high efficiency and flexibility and is favored by many scholars.In actual seru production,it is an important step to make a schedule of order reasonably to improve the seru production efficiency,considering the constraints of renewable resources such as multi-skilled workers.This paper first introduces the research background,significance and research status,expounds the concept of seru production system,briefly summarizes the practical application of seru,and then introduces three basic types of seru: divisional seru,rotating seru and yatai.Considering that there is little seru scheduling research with constraints of multi-skilled workers,combined with a lot of factors which can affect the scheduling,three seru scheduling problem with constraints of multi-skilled workers are studied.First,a scheduling problem considering lot-splitting in rotating seru is discussed.It is assumed that when the types of processed product changes,the setup time will be generated.According to the characteristics of worker assignment and order allocation,an improved genetic algorithm is proposed to solve the problem.In order to improve the performance of the proposed algorithm,a chromosome coding form composed of three different features is designed.A numerical example is taken and computed to validate the effectiveness of proposed model and algorithm.Secondly,a seru scheduling problem considering learning effect is taken into account.Processing time is related to processing position and constraint of multi-skilled workers is presented by the execute mode.A genetic particle swarm optimization algorithm is proposed to solve the problem.The particle update mechanism,crossover operator and mutation operator are combined to improve the calculation speed and accuracy of the algorithm.A numerical example is presented to verify the effectiveness of hybrid algorithm.Finally,a seru scheduling problem with random processing time is discussed.The position dependent processing time,learning effect and deterioration effect is considered.And the setup time is assumed to be related to the types of adjacent products.The position dependent processing time is affected by learning effect and deterioration effect.The setup time is related to the types of adjacent products.The randomness of processing time is described by normal distribution and uniform distribution.A genetic simulated annealing algorithm is proposed to solve the problem.Simulated annealing operation based on neighborhood search structure is designed with two different search methods for local search.Sensitivity analysis and numerical experiments are carried out to validate the effectiveness and efficiency of the proposed model and algorithm.Production scheduling is an important decision-making activity for enterprises to improve the production efficiency and resource of multi-skilled worker is a key influencing factor.Therefore,this paper studies seru scheduling problems with constraint of multi-skilled worker by establishing reasonable mathematical model and designing effective optimization algorithms which has theoretical and practical significance.