Retail order automatic packing method based on hybrid genetic spotted serow optimization algorithm

• Main Authors: LI QUANLIANG, YANG HONGJUN, ZHOU WENHONG, ZHU LING, YAO ZHENGYA, WANG XIAOFANG, QUAN YINGYU, WANG YUMEI, YUE HUA, LENG SHUNTIAN, WANG FANG
• Format: Patent
• Language: Chinese; English
• Published: 08.11.2022
• 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; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention discloses a cigarette retail order automatic packing method based on a hybrid adaptive genetic spotted serow optimization algorithm, and the method comprises the steps: 1, planning a cigarette automatic packing overall design process, and determining an optimization target, variables, constraint conditions, and the correlation between size data; 2, establishing a multi-objective optimization model with priority for an actual cigarette packing problem, and performing quantitative expression on multiple constraint conditions in an actual operation process; and step 3, improving the spotted serow optimization algorithm by using an improved adaptive genetic algorithm and a chaos initialization and roulette selection strategy, and solving a cigarette packing model through the obtained hybrid adaptive genetic spotted serow optimization algorithm to obtain an optimal scheme for automatic packing of cigarette retail orders. The embodiment of the invention provides an optimization algorithm for automatic