{"title":"水泥工业多基地协同制造集成计划调度模型及优化仿真","authors":"Xiaoxue Shang, Changchun Pan","doi":"10.1109/TOCS56154.2022.10016150","DOIUrl":null,"url":null,"abstract":"This paper aims at the multi-base cooperative production and scheduling problem in cement industry. Considering the supply of raw materials, manufacturing capacity of production lines, inventory capacity and customer demand, a MIP (Mixed Integer Programming) model is established. Then AMPL (A Mathematical Programming Language) is used to formally describe this MIP optimization model. The problem then is solved by Gurobi solver. Finally, the collaborative optimization problem is visually configured and solved based on the developed network collaborative manufacturing simulation software platform. The computational results verify the effectiveness of the optimization problem modeling and the feasibility of the simulation platform.","PeriodicalId":227449,"journal":{"name":"2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrated Planning & Scheduling Model and Optimization Simulation of Multi-base Collaborative Manufacturing for Cement Industry\",\"authors\":\"Xiaoxue Shang, Changchun Pan\",\"doi\":\"10.1109/TOCS56154.2022.10016150\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper aims at the multi-base cooperative production and scheduling problem in cement industry. Considering the supply of raw materials, manufacturing capacity of production lines, inventory capacity and customer demand, a MIP (Mixed Integer Programming) model is established. Then AMPL (A Mathematical Programming Language) is used to formally describe this MIP optimization model. The problem then is solved by Gurobi solver. Finally, the collaborative optimization problem is visually configured and solved based on the developed network collaborative manufacturing simulation software platform. The computational results verify the effectiveness of the optimization problem modeling and the feasibility of the simulation platform.\",\"PeriodicalId\":227449,\"journal\":{\"name\":\"2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TOCS56154.2022.10016150\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TOCS56154.2022.10016150","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
本文针对水泥行业多基地协同生产调度问题进行了研究。考虑原材料供应、生产线制造能力、库存能力和客户需求,建立了混合整数规划模型。然后用数学规划语言AMPL (A Mathematical Programming Language)对MIP优化模型进行形式化描述。然后用Gurobi求解器求解问题。最后,基于开发的网络协同制造仿真软件平台,对协同优化问题进行了可视化配置和求解。计算结果验证了优化问题建模的有效性和仿真平台的可行性。
Integrated Planning & Scheduling Model and Optimization Simulation of Multi-base Collaborative Manufacturing for Cement Industry
This paper aims at the multi-base cooperative production and scheduling problem in cement industry. Considering the supply of raw materials, manufacturing capacity of production lines, inventory capacity and customer demand, a MIP (Mixed Integer Programming) model is established. Then AMPL (A Mathematical Programming Language) is used to formally describe this MIP optimization model. The problem then is solved by Gurobi solver. Finally, the collaborative optimization problem is visually configured and solved based on the developed network collaborative manufacturing simulation software platform. The computational results verify the effectiveness of the optimization problem modeling and the feasibility of the simulation platform.