Application Of Improved Ant Colony Algorithm For The Rubber Vulcanization Workshop

The tire manufacturing industry is a large-scale industry with intensive productionresources and labor, and a good production plan is of great significance to the productionprocess and the actual income.In tire production, the quality of vulcanization workshopscheduling plan directly affects the efficiency of the whole production process, so thispaper mainly studies the vulcanizing workshop production scheduling problem.First, this paper introduces the research status of job shop scheduling,, including thestudy of the classification and characteristics of job shop scheduling, research methodsand its development trend.Secondly, studies the production features of the vulcanization workshop, andaccording to the actual situation of the vulcanization workshop, establishes themathematical model of it.Thirdly, According to characteristics of vulcanization workshop scheduling problemand in order to avoid the shortcomings of ant algorithm fall into local best situation easily,this paper presents an improved ant colony algorithm. The genetic algorithm will beintegrated into each iteration of ant colony algorithm to strengthen the ability of localsearch algorithms and maintain the diversity of solutions. In order to improve theefficiency of solution,using ant colony algorithm characteristics of positive feedback tostrengthen the convergence rate of the whole algorithm.Then, taking a vulcanizationworkshop production team as an example,simulation was implemented by using improvedant colony algorithm, the results show that the proposed algorithm in terms of solutionquality and convergence rate are more effective than ACS algorithm and GAAAalgorithm.Then, according to characteristics of multi-object vulcanization workshop schedulingproblem,design and improve the function of the algorithm to meet the needs of solvingmulti-objective problem. Through simulation experiments, the algorithm in terms ofsolution quality and convergence are more effective than MACS algorithm and MOGAalgorithm.Finally, for study on the production scheduling of vulcanization workshop in dynamic and uncertain environments, in this paper, taking vulcanizing machine fault as anexample, with combine the improved ant colony algorithm and rolling schedulingtechnology, this scheduling problem is solved successfully and simulation results is veryeffective.