Multi-objective Scheduling Optimization Of Resource Sharing Under Network Cooperative Manufacturing

At present,the research on network coordination is mainly focused on collaborative design,collaborative innovation,collaborative manufacturing platform architecture and selection mechanism,but there is little research on the relationship between network co-manufacturing enterprises.Latest study,scholars believe that the enterprise is linked together with different chain structure,this paper creatively combines the chain of command and the value chain and supply chain structure and analyses enterprise competition game relation under the network environment of collaborative manufacturing chain,and architecture by using the method of dynamic game to build the game model between enterprises,analyzes the influence factors of affecting enterprise game strategy choice.This paper further clarifies the evolutionary path of the network collaborative manufacturing system through the evolutionary game method,and studies the different methods affecting the system evolution by changing different variables,including changing the initial state and influencing factors of the system evolution.Through the above research,it is found that an excellent resource scheduling scheme plays a crucial role in the sustainable development of collaborative manufacturing system.Therefore,this paper studies the multi-objective optimization model of network collaborative manufacturing resource scheduling.Fully considering the complex sequential relationship between parallel and serial sub-tasks in the collaborative manufacturing environment,the manufacturing companies are spatially heterogeneous and the production targets require diverse features.the multi-objective optimization model of task scheduling improves the NSGA-II algorithm and adopts a reasonable and efficient coding and decoding method,genetic operators and elite strategies.It can increase the computing speed while ensuring the diversity of the population,and finally obtains multiple solutions.The effectiveness of the proposed method is verified by numerical examples.