Research And Application Of Improved Bacterial Foraging Algorithm In Job Shop Scheduling

With the development of economy,the competition in market is more and more fierce,Manufacturing is an important industry of national economy development,the traditional manufacturing mode is difficult to meet people’s diverse needs.Production scheduling module is the core module in the manufacturing process.It has crucial influence in productivity and cost of production as well as the comprehensive competitiveness to enterprise.So in order to improve efficiency of manufacturing system,deal with the rapid development of economy,and increasing update of technology science,the study of solving scheduling problem has important value.Shop scheduling problem is a kind of NP-hard problem.These algorithms to deal with the problem of shop scheduling has achieved many good results,but due to the size of the problem and the procedure is more complex,are greatly influenced by the process conditions.These traditional optimization can only handle small scheduling problem.To massive problems,the effect is not good.Therefore.According to the feeding process of e.coli.Bacteria foraging algorithm as a type of intelligence optimization algorithm was presented.Domestic and foreign researchers attempt to apply the algorithm to the workshop scheduling problem,and some results have been achieved,there are also researchers aiming at the advantages and disadvantages of various algorithms,hybrid optimization algorithm,and achieved good results.Paper first studied the job shop scheduling problem.Analyzed the current research in detail.In the further study of standard bacteria foraging optimization algorithm on the basis of analysis algorithm existing problems and advantages,combined with the characteristics of the workshop scheduling problem,an improved bacteria foraging optimization algorithm,and apply it to solve the workshop scheduling problem.Improved algorithm focus on chemotactic movement step operation and reverse direction is improved,design the adaptive step length in the change in three cases,and strengthen the global optimal position and the position in the reverse direction of individual optimal guidance,avoid premature phenomenon of the algorithm.Through compare the experimental results with the standard algorithm,PSO algorithm,analyzed the performance of improved algorithm.At the same time,verified robustness and the feasibility of the proposed algorithm used in JSP.The results show that the improved bacteria foraging optimization algorithm improved thespeed of convergence in solving small problems,and is obviously better than the performance of standard algorithm in solving the size of the shop scheduling problem.