It is difficult for the double suppression division algorithm of bee colony to solve the spatio-temporal coupling or have higher dimensional attributes and undertake sudden tasks.Using the idea of clustering,after clu...It is difficult for the double suppression division algorithm of bee colony to solve the spatio-temporal coupling or have higher dimensional attributes and undertake sudden tasks.Using the idea of clustering,after clustering tasks according to spatio-temporal attributes,the clustered groups are linked into task sub-chains according to similarity.Then,based on the correlation between clusters,the child chains are connected to form a task chain.Therefore,the limitation is solved that the task chain in the bee colony algorithm can only be connected according to one dimension.When a sudden task occurs,a method of inserting a small number of tasks into the original task chain and a task chain reconstruction method are designed according to the relative relationship between the number of sudden tasks and the number of remaining tasks.Through the above improvements,the algorithm can be used to process tasks with spatio-temporal coupling and burst tasks.In order to reflect the efficiency and applicability of the algorithm,a task allocation model for the unmanned aerial vehicle(UAV)group is constructed,and a one-to-one correspondence between the improved bee colony double suppression division algorithm and each attribute in the UAV group is proposed.Task assignment has been constructed.The study uses the self-adjusting characteristics of the bee colony to achieve task allocation.Simulation verification and algorithm comparison show that the algorithm has stronger planning advantages and algorithm performance.展开更多
The microservices architecture has been proposed to overcome the drawbacks of the traditional monolithic architecture.Scalability is one of the most attractive features of microservices.Scaling in the microservices ar...The microservices architecture has been proposed to overcome the drawbacks of the traditional monolithic architecture.Scalability is one of the most attractive features of microservices.Scaling in the microservices architecture requires the scaling of specified services only,rather than the entire application.Scaling services can be achieved by deploying the same service multiple times on different physical machines.However,problems with load balancing may arise.Most existing solutions of microservices load balancing focus on individual tasks and ignore dependencies between these tasks.In the present paper,we propose TCLBM,a task chainbased load balancing algorithm for microservices.When an Application Programming Interface(API)request is received,TCLBM chooses target services for all tasks of this API call and achieves load balancing by evaluating the system resource usage of each service instance.TCLBM reduces the API response time by reducing data transmissions between physical machines.We use three heuristic algorithms,namely,Particle Swarm Optimization(PSO),Simulated Annealing(SA),and Genetic Algorithm(GA),to implement TCLBM,and comparison results reveal that GA performs best.Our findings show that TCLBM achieves load balancing among service instances and reduces API response times by up to 10%compared with existing methods.展开更多
An agile supply chain can be defined as a dynamic s up ply network of some autonomous or semi-autonomous business entities, which can well adapt to the competitive, cooperative and dynamic market environment Agile sup...An agile supply chain can be defined as a dynamic s up ply network of some autonomous or semi-autonomous business entities, which can well adapt to the competitive, cooperative and dynamic market environment Agile supply chain needs quick response ability to the unpredictable and ever-changin g market environment, and the entities in agile supply chain have complex relati onships of competition, cooperation and dynamics, which make agile supply chain management a very complex process that includes a lot of no-linear, dynamic and uncertain factors. There is a common opinion that applying multi-agent collaborative work environm ent is an appropriate method to solve agile supply chain management problem. We have presented a model based on coordination of Multi-Agent System (MAS) two ye ars ago, and it has already been proved to be a rather better model by practical project. In the model, we apply MAS structure, and agents negotiate each other to achieve coordination, so the communication among agents becomes very impo rtant. Task allocation is a very common problem in agile supply chain management, and t here are many complex task re-allocation problems at the transaction level. In such situations, agents need to negotiate with others to produce effective alloc ation results. But traditional negotiation mechanisms often cease to work as a r esult of communication or computational complexities. Auctions provide an effici ent way of resolving one-to-many negotiations, so in this paper, we choose Eng lish auction to design a sufficient negotiation mechanism, and use combinatorial auction to solve the complex task re-allocation problems. We first analyze the features of task allocation problems in agile supply chain and build a problem model, and then design a comprehensive task allocation mechanism based on auctio n theories. Finally, by examining our results for what it is, essentially, an ap plication of game-theory and mechanism design to existing application, we draw some general conclusions on how such concepts can be operationalized in automate d agents. Some further research on the problem is also discussed.展开更多
基金This work was supported by the National Natural Science and Technology Innovation 2030 Major Project of Ministry of Science and Technology of China(2018AAA0101200)the National Natural Science Foundation of China(61502522,61502534)+4 种基金the Equipment Pre-Research Field Fund(JZX7Y20190253036101)the Equipment Pre-Research Ministry of Education Joint Fund(6141A02033703)Shaanxi Provincial Natural Science Foundation(2020JQ-493)the Military Science Project of the National Social Science Fund(WJ2019-SKJJ-C-092)the Theoretical Research Foundation of Armed Police Engineering University(WJY202148).
文摘It is difficult for the double suppression division algorithm of bee colony to solve the spatio-temporal coupling or have higher dimensional attributes and undertake sudden tasks.Using the idea of clustering,after clustering tasks according to spatio-temporal attributes,the clustered groups are linked into task sub-chains according to similarity.Then,based on the correlation between clusters,the child chains are connected to form a task chain.Therefore,the limitation is solved that the task chain in the bee colony algorithm can only be connected according to one dimension.When a sudden task occurs,a method of inserting a small number of tasks into the original task chain and a task chain reconstruction method are designed according to the relative relationship between the number of sudden tasks and the number of remaining tasks.Through the above improvements,the algorithm can be used to process tasks with spatio-temporal coupling and burst tasks.In order to reflect the efficiency and applicability of the algorithm,a task allocation model for the unmanned aerial vehicle(UAV)group is constructed,and a one-to-one correspondence between the improved bee colony double suppression division algorithm and each attribute in the UAV group is proposed.Task assignment has been constructed.The study uses the self-adjusting characteristics of the bee colony to achieve task allocation.Simulation verification and algorithm comparison show that the algorithm has stronger planning advantages and algorithm performance.
文摘The microservices architecture has been proposed to overcome the drawbacks of the traditional monolithic architecture.Scalability is one of the most attractive features of microservices.Scaling in the microservices architecture requires the scaling of specified services only,rather than the entire application.Scaling services can be achieved by deploying the same service multiple times on different physical machines.However,problems with load balancing may arise.Most existing solutions of microservices load balancing focus on individual tasks and ignore dependencies between these tasks.In the present paper,we propose TCLBM,a task chainbased load balancing algorithm for microservices.When an Application Programming Interface(API)request is received,TCLBM chooses target services for all tasks of this API call and achieves load balancing by evaluating the system resource usage of each service instance.TCLBM reduces the API response time by reducing data transmissions between physical machines.We use three heuristic algorithms,namely,Particle Swarm Optimization(PSO),Simulated Annealing(SA),and Genetic Algorithm(GA),to implement TCLBM,and comparison results reveal that GA performs best.Our findings show that TCLBM achieves load balancing among service instances and reduces API response times by up to 10%compared with existing methods.
文摘An agile supply chain can be defined as a dynamic s up ply network of some autonomous or semi-autonomous business entities, which can well adapt to the competitive, cooperative and dynamic market environment Agile supply chain needs quick response ability to the unpredictable and ever-changin g market environment, and the entities in agile supply chain have complex relati onships of competition, cooperation and dynamics, which make agile supply chain management a very complex process that includes a lot of no-linear, dynamic and uncertain factors. There is a common opinion that applying multi-agent collaborative work environm ent is an appropriate method to solve agile supply chain management problem. We have presented a model based on coordination of Multi-Agent System (MAS) two ye ars ago, and it has already been proved to be a rather better model by practical project. In the model, we apply MAS structure, and agents negotiate each other to achieve coordination, so the communication among agents becomes very impo rtant. Task allocation is a very common problem in agile supply chain management, and t here are many complex task re-allocation problems at the transaction level. In such situations, agents need to negotiate with others to produce effective alloc ation results. But traditional negotiation mechanisms often cease to work as a r esult of communication or computational complexities. Auctions provide an effici ent way of resolving one-to-many negotiations, so in this paper, we choose Eng lish auction to design a sufficient negotiation mechanism, and use combinatorial auction to solve the complex task re-allocation problems. We first analyze the features of task allocation problems in agile supply chain and build a problem model, and then design a comprehensive task allocation mechanism based on auctio n theories. Finally, by examining our results for what it is, essentially, an ap plication of game-theory and mechanism design to existing application, we draw some general conclusions on how such concepts can be operationalized in automate d agents. Some further research on the problem is also discussed.
文摘目前,多无人机(Unmanned Aerial Vehicle,UAV)在大规模任务场景下的任务分配问题仍是一个挑战性问题。传统启发式算法可在较低计算复杂度下得到满意的解,但收敛速度慢且难以收敛到全局最优解。为此提出一种基于UAV链、任务链和双阶段修复策略的遗传算法(Genetic Algorithm Based on UAV-chain,Task-chain,and Two-Stage Repair strategy,UTTSRGA)。在编码结构中设计UAV链和任务链来量化任务执行代价,增强了编码中的信息承载能力并显著提升搜索效率。针对交叉操作后出现任务缺失与任务重复问题,设计双阶段修复策略。第一阶段设计随机填充机制,增强对解空间的全局搜索能力;第二阶段设计邻接映射表修复机制,根据任务间的邻接关系提供进化方向,有效引导种群向当前最优解快速收敛。提出动态复合变异策略,融合自适应变异率与基于任务链值的变异点选择,并设计4种功能互补的变异算子,多维度协同优化解的质量。针对大规模场景下的路径交叉问题,引入路径优化策略,从实践角度进一步优化任务分配方案。实验结果表明,UTTSRGA在不同任务规模下,尤其是大规模复杂任务场景中,在解的质量、收敛速度和鲁棒性3个方面均表现出显著优势。
