Optimization Of Chemical Industry Batch Process System Based On Artificial Intelligence Algorithm

The optimization of chemical batch process system plays an important role in production line optimization design,production scheduling research and green production.It provides an important tool for chemical plants to save money,optimize production time,and actively respond to market demand,which guarantees the chemical plants to cope with the challenges brought by economic globalization.In this paper,the design of batch process and production scheduling are taken as the direction,and the intelligent algorithm is combined to carry out the following research:Firstly,the single product process was modeled by using enumeration and backtracking method,and the optimal combination based on the model was obtained.Then,the process was remodeled using an improved genetic algorithm.Through the addition of penalty operation and self-optimization mechanism,the search space of the model was not restricted and the individuals in the population were optimized,a stable final result that meets the requirements was obtained.Secondly,the particle swarm optimization algorithm and genetic algorithm were used to study the scheduling and design in the multiproduct batch process.Through the particle swarm optimization algorithm,the optimal production sequencing and the limit cycle time of the process were obtained.And then the limited cycle time was taken as a known condition into the model established by genetic algorithm to study the design process.Finally,the genetic algorithm was used to model the multipurpose batch process.The coding of the model population was used a combination of decimal coding and binary coding,which not only solves the problem of calculation caused by too many digits in chromosomes,but also avoids the risk that some variables may fall into local optimality due to the limitation of the search space.In addition,a concession operation was added to the model to enable the population to continue to evolve even when it is at a disadvantage during the breeding process,avoiding the risk of being eliminated.In this paper,intelligent algorithm is used to model three kinds of common batch plants.Through the analysis and comparison of the model and the results,it provides a reference for the future research on system optimization and the selection of production methods for batch plants.In addition,the model framework involved in this paper and some improvements to the algorithm have certain guiding significance for future research.