Application Of Improved Niche Genetic Algorithm On Job-shop Scheduling

The workshop as the execution unit of the machine-finishing enterprise creates profit has been continuously pay attention, but at present the proportion of workshop uses in the non-workable time to the total time is bigger. At the very long time the job is flowing at waiting processing, and the workshop dispatcher is unable to have the very good complete control of the job, frequently appears the dispatcher not to know at present each engine is processing, and what the next step is. Regarding to the high level leader wants to have understood enterprise's concrete processing situation, is more difficult. JSP belonging to NP-hard problem is the hardest solving problem in classic optimization problem. GA is applied in the optimization of JSP widely, because it has characteristics that it can be used generally and the algorithm is simple. But the characteristic of strongly general using leads to badly flexibility. For the algorithm is simple though it can guarantee its entire convergence, it will essentially degenerate in part.In view of the standard heredity algorithm precocious question, niche technology was considered to be one effective method, it may maintain the population multiplicity, can strengthen the new search region the detect ability. Uses niche technology is based to inherit the similarity to gather in the population the individual fitness on the function several mountains peaks, and then parallel let's GA investigate these mountain peaks. Therefore in the population the individual on is dispersed to the entire search space in, like this can when the population iteration effectively maintains the certain multiplicity.This article prime task is: In view of the shortcoming of the traditional niche technology based on the individual fitness sharing which could not effectively use the factor of merit in the community, in the union of biology population evolution theory, this paper proposed one kind the improvement niche genetic algorithm which based on the populations-sharing, which have fully considered population mutually influence and restricts relations in the evolution process, have effectively used the fine population's characteristic, other population fitness bases shared-population's fitness to adjust. Improvement population's quality thus causes the evolution process to develop along a more superior direction, has effectively avoided the precocious phenomenon, and improved the algorithm's restriction.At present, the algorithm is successfully applied to "the job-shop scheduling simulation system", carries on the solution in view of some transportation equipment manufacture enterprise's production line actual data, has obtained the good effect.