Job Shop Scheduling Technology For Processing Matching, Same-time-stop And Multi-level Relevance Resources Scheduling Constraints

Job shop scheduling is the effective means to realize optimal allocation of resources.At this time, the efficient heuristic algorithm and the genetic algorithm, which is skilled inglobal optimization, become supporting methods to job shop scheduling of complexscheduling constraints. With the job shop scheduling of manufacturing enterprises haschanged into high efficiency and complication, the research about processing ordinaryscheduling constraints is hard to meet requirements of processing the complex schedulingconstraints. Thus, combined the actual workshop operation requirements, this paper set themanufacturing system object as processing matching, same-time-stop and multi-levelrelevance resources scheduling constraints, on the theory of genetic algorithm and heuristicalgorithm. These algorithms for processing complex constraints are researched and proposedcombination of theory and practice in this paper. And then the practical software isdeveloped based on job shop scheduling technology for processing complex schedulingconstraints and the research result is validated by using the software in practical projects.Main contents of this paper are as follows:(1) Using production mode of discrete product type as research background, the jobshop scheduling theory facing practical production process is analyzed. At same time, thegenetic algorithm and heuristic algorithm are proposed as the core of new schedulingmethod to solve complex constraints, and its technology framework, function model andbusiness procedure are studied. Two core technologies are proposed, including processingtechnology of matching and same-time-stop scheduling constraints based on geneticalgorithm, processing technology of multi-level relevance resources based on heuristicalgorithm.(2)Aiming at the non-independent processes and non-exclusive resources occupationof JSPP, the processing technology of matching and same-time-stop scheduling constraintsbased on the improved genetic algorithm was presented. After analyzing matching, batchprocessing, process sequence and machine constraints, the target model thinking aboututilization rate of batch processing machines and average delay time of tasks was built. Tosolve matching and batch processing constraints, a two-dimensional encoding chromosomewas designed and the processing procedure of scheduling constraints based on geneticalgorithm was presented. To meet scheduling constraints, the adjustment mechanism of job sequence chromosome meeting matching constraint was presented and the adjustmentmechanism of blending chromosome meeting dynamic process combination was raised.The same-time-stop constraint within processes is well solved.(3) Aiming at multi-level relevance resources constraint, the processing technology forthis constraint based on heuristic algorithm was presented, which meets the matchingrelationship between multi-level relevance resources and selects the best combination ofmulti-level relevance resources. Then scheduling time calculation for multi-level relevanceresources processes is proposed.(4) Based on requirements of manufacturing enterprises, the job shop schedulingsoftware for processing complex scheduling constraints is developed. Through testing inproject application, the research achievement of this paper is validated.