Scheduling Of A Single Batch Processing Machine With Energy Cost Consideration And Its Algorithm Research

Production scheduling is indispensable during the production and manufacturing of enterprises,and it is the key to the overall operation of manufacturing enterprises.Batch scheduling,as a modern scheduling method,is widely used in various fields.However,with the rapid development of science and technology,the rising value of energy,the reducing of resource volume and environmental problems,the increasing complexity of enterprises' actual optimizing problems,vast energy consuming demand and energy wasting problems of manufacturing enterprises,all have brought great constraints on the survival and development of manufacturing enterprises.At the same time,the globalization of competition and market changes make the enterprises hard to adapt the long-term production requirement by using traditional production method,so companies need to change the mode of production,complete the production scheduling problem as a whole and optimization by the modern technology and methods,meanwhile,consider workshop production efficiency and energy consumption problems,quickly allocate the scheduling resources,work out scheduling plans,improve enterprise efficiency,reduce energy consumption,and manage the problems to be deal with urgently that manufacturing enterprises face.Aiming at the production scheduling problems in enterprise workshop,this paper studies the single batch scheduling problem with the consideration of energy cost.Firstly,illustrate the batch scheduling background systematically,summarize thoroughly the existing literature about considering production efficiency and energy consuming problems,and have a further introduction about the single batch scheduling problem of energy consumption solved in this paper.Then,by establishing mathematical model on research problems,apply respectively simulated annealing algorithm and genetic algorithm to the target problem solving,through the simulation experiment to test the proposed model and to have a comparison and analysis of the experimental data.This paper has a deep respective analysis of the simulated annealing algorithm and genetic algorithm application of production scheduling problems,to make model for solving problems,consider the state of the machine and state transformations between machines,during the energy consumption cost calculation,adopt time-of-use electricity price standard,use changeable electricity prices combined with machine state transfer model to save cost for manufacturing enterprise.In the simulated annealing algorithm,optimization solution performance of the algorithm is improved by improving the acceptance-rejection principle in annealing algorithm.In genetic algorithm,through the algorithm selection operator,improve the method for calculating the new individual fitness value to avoid the "premature" problems of the genetic algorithm,thus improve the optimization solution performance of algorithm.