Dynamic clustering algorithm specification allocation method based on genetic simulated annealing algorithm

• Main Authors: WANG LU, ZHANG LIANG, YANG JIAO, WANG JINBING, PU RUIQIANG, LI SHAOBO
• Format: Patent
• Language: Chinese; English
• Published: 26.03.2024
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; ELECTRIC DIGITAL DATA PROCESSING; PERFORMING OPERATIONS; PHYSICS; POSTAL SORTING; SEPARATING SOLIDS FROM SOLIDS; SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTEDPIECE-MEAL, e.g. BY PICKING; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR; TRANSPORTING

The invention discloses a dynamic clustering algorithm specification allocation method based on a genetic simulated annealing algorithm. The method comprises the following steps: step 1, determining a specification similarity coefficient # imgabs0 # between partitions; step 2, optimization modeling of specification allocation: solving a minimum value of a specification similarity coefficient and an accumulated value of each partition, wherein an objective function is # imgabs 1 #; step 3, solving of a specification allocation model: combining a genetic algorithm and a simulated annealing algorithm (SAGA) for optimizing a K-means clustering algorithm. According to the product specification distribution method, the positions of the cigarette bins distributed according to different cigarette product specifications are reasonably arranged according to the change of the product specifications and the number in the order, so that the efficiency of a sorting system is improved, and the sorting completion time is sho