Research Of Hybrid Assembly Line Balancing And Job Shop Scheduling Under Uncertain Conditions

In the modern manufacturing mode, there are more and more variety and small batchesproduction,lower cost and higher quality,so standardization and fine are put forward formanufacturing workshop operation management, which cause that managers increasingly focuson existed uncertainty in the production and its impact on the production.The information thatget in the practical work is not timely or incomplete.Because science and technology and marketchange quickly,in order to respond to these challenges,it put forward a higher and morestringent requirements for Workshop’s uncertain scheduling method and technology.Productionscheduling need understand it in a timely manner and taking into full account these factorsfully,this will prevent and eliminate the imbalanced danger in production,the scheduling schemein the execution process needs to dynamically adjust to these changes at any time.Based on the summaries of the past work,this parer puts forward the frame and mechanismfor uncertain dynamic scheduling, analyzes the impact on production process cased by uncertaininformation, proposes robust scheduling method and dynamical adaptive reactive strategy underuncertainty and explores the uncertain information processing and parameter correction methodin the production process.The main work and research results are shown as follows:This paper analyzes dynamic scheduling mechanism under uncertain environment, comesup with the overall scheduling framework combined with the scheduling of proactive andreactive scheduling, set robust scheduling with uncertain absorption capacity as thepre-scheduling scheme before start of the production, take the strategy combined withevent-driven strategy and the receding horizon in production, develop the adaptive responsescheduling algorithm in response to emergencies, and use Bayesian filtering algorithm toreprocess and correct uncertain information to provide a more reliable basis for decision makingfor pre-scheduling in the next phase.Concerning assembly line balancing problem and more universal job shop schedulingproblems,this paper analyzes the robust scheduling method that has uncertain absorption capacity.For the assembly line balancing problem, this paper establishes a robust integer linearprogramming model that can cope with the problems with uncertain operation time parameters.this paper establishes goal programming model based scheduling target expectations and developthe intelligent algorithm for job shop scheduling problem to solve the problem.Concerning the emergencies and disturbances in the production process, this paperinvestigate reactive scheduling method. This paper develop adaptive double-coded geneticalgorithm for flexible job shop scheduling problem.According to the universal computational complexity for the scheduling problem,this paper develops two fast algorithms-G plus algebraic method for assembly line scheduling problem and hopfield neural network algorithm for job shop scheduling problem.For the former,the assembly line balancing problem is equivalent to the traveling salesman problem proved bymathematical proposition in the sense of G plus algebraic. For the latter, Convergence of themethod is proved based on Lyapunov stability theory. And the effectiveness of the two methodsis verified.This part researches on processing method for uncertain information and the correctionmethods for the uncertain parameters.Concerning the uncertain parameters in the productionoperating system, this paper set Bayesian theory as a tool, use production data in the posterior tocorrect Prior statistical distribution parameters in order to obtain a more realistic distribution ofthe parameters and provide a reliable guarantee for accuracy and precision in the followingproduction process.