Research On Multi-objective And Multi-stage Scheduling For Equipment Resource In Cloud Manufacturing

As a kind of intelligent manufacturing mode based on network and service orientation,cloud manufacturing makes use of network and service platform to manage and schedule manufacturing resources uniformly,and provides users with all kinds of on-demand products and services with high efficiency and low cost.In order to optimize scheduling equipment resources in the cloud manufacturing environment,this paper selects cloud services which in different geographies to complete the sub-tasks of manufacturing after decentralized,and deeply studied the multi-objective and multi-stage scheduling of equipment resource and sub-task.The main contents are as follows:According to the dispersion,diversity and heterogeneity of cloud equipment resources,this paper uses a unified language to describe and encapsulate.For small batch customization and structure is not uniform of manufacturing tasks,In this paper,decompose task based on resource service information and task dependency.In order to maximize the multistage benefits in process of cloud equipment resource scheduling,this paper divides the scheduling into two stages,the multi-objective scheduling of enterprise resource with coarse-grained sub-tasks and the multi-objective scheduling of shop-level resources with fine-grained subtasks.Aiming at multi-objective scheduling of enterprise resource,a multi-objective scheduling model with low manufacturing cost,short manufacturing time and high manufacturing quality is constructed,an improved particle swarm optimization algorithm based on hybrid frog leaping algorithm and artificial bee colony algorithm is designed.Aiming at the multi-objective scheduling of shop-level resources,constructed a multi-objective scheduling model with low manufacturing cost,low manufacturing time and ratio manufacturing equipment load,an improved particle swarm optimization which based on genetic algorithm is adopted.The validity,accuracy and speed of these two algorithms are verified by examples.Based on the above research,the author has developed a cloud equipment resource platform,users can publish and apply equipment resources on the platform,and optimize the dispatching of resources and services on the platform.The last running example shows how to use the platform.