This paper addresses the problem of service composition in military organization cloud cooperation（MOCC）. Military service providers（MSP） cooperate together to provide military resources for military service users...This paper addresses the problem of service composition in military organization cloud cooperation（MOCC）. Military service providers（MSP） cooperate together to provide military resources for military service users（MSU）. A group of atom services, each of which has its level of quality of service（QoS）, can be combined together into a certain structure to form a composite service. Since there are a large number of atom services having the same function, the atom service is selected to participate in the composite service so as to fulfill users＇ will. In this paper a method based on discrete particle swarm optimization（DPSO） is proposed to tackle this problem. The method aims at selecting atom services from service repositories to constitute the composite service, satisfying the MSU＇s requirement on QoS. Since the QoS criteria include location-aware criteria and location-independent criteria, this method aims to get the composite service with the highest location-aware criteria and the best-match location-independent criteria. Simulations show that the DPSO has a better performance compared with the standard particle swarm optimization（PSO） and genetic algorithm（GA）.展开更多
Scheduling is one of the most difficult issues in t he planning and operations of the aircraft services industry. In this paper, t he various scheduling problems in ground support operation of an aircraft mainte nance...Scheduling is one of the most difficult issues in t he planning and operations of the aircraft services industry. In this paper, t he various scheduling problems in ground support operation of an aircraft mainte nance service company are addressed. The authors developed a set of vehicle rout ings to cover each schedule flights; the objectives pursued are the maximization of vehicle and manpower utilization and minimization of operation time. To obta in the goals, an integer-programming model with genetic algorithm is formulated . It is found that the company can produce an effective and efficient schedules to deploy the manpower and equipment resources. Simulation is used to verify the method and a MATLAB program is used to code the genetic algorithm. This model i s further illustrated by a case study in Hong Kong and the benefit elaborated. F inally, a conclusion is made to summarize the experience of this project and pro vide further improvement.展开更多
Based on the deficiency of time convergence and variability of Web services selection for services composition supporting cross-enterprises collaboration,an algorithm QCDSS(QoS constraints of dynamic Web services sele...Based on the deficiency of time convergence and variability of Web services selection for services composition supporting cross-enterprises collaboration,an algorithm QCDSS(QoS constraints of dynamic Web services selection)to resolve dynamic Web services selection with QoS global optimal path,was proposed.The essence of the algorithm was that the problem of dynamic Web services selection with QoS global optimal path was transformed into a multi-objective services composition optimization problem with QoS constraints.The operations of the cross and mutation in genetic algorithm were brought into PSOA(particle swarm optimization algorithm),forming an improved algorithm(IPSOA)to solve the QoS global optimal problem.Theoretical analysis and experimental results indicate that the algorithm can better satisfy the time convergence requirement for Web services composition supporting cross-enterprises collaboration than the traditional algorithms.展开更多
基金supported by the National Natural Science Foundation of China(61573283)
文摘This paper addresses the problem of service composition in military organization cloud cooperation（MOCC）. Military service providers（MSP） cooperate together to provide military resources for military service users（MSU）. A group of atom services, each of which has its level of quality of service（QoS）, can be combined together into a certain structure to form a composite service. Since there are a large number of atom services having the same function, the atom service is selected to participate in the composite service so as to fulfill users＇ will. In this paper a method based on discrete particle swarm optimization（DPSO） is proposed to tackle this problem. The method aims at selecting atom services from service repositories to constitute the composite service, satisfying the MSU＇s requirement on QoS. Since the QoS criteria include location-aware criteria and location-independent criteria, this method aims to get the composite service with the highest location-aware criteria and the best-match location-independent criteria. Simulations show that the DPSO has a better performance compared with the standard particle swarm optimization（PSO） and genetic algorithm（GA）.
文摘Scheduling is one of the most difficult issues in t he planning and operations of the aircraft services industry. In this paper, t he various scheduling problems in ground support operation of an aircraft mainte nance service company are addressed. The authors developed a set of vehicle rout ings to cover each schedule flights; the objectives pursued are the maximization of vehicle and manpower utilization and minimization of operation time. To obta in the goals, an integer-programming model with genetic algorithm is formulated . It is found that the company can produce an effective and efficient schedules to deploy the manpower and equipment resources. Simulation is used to verify the method and a MATLAB program is used to code the genetic algorithm. This model i s further illustrated by a case study in Hong Kong and the benefit elaborated. F inally, a conclusion is made to summarize the experience of this project and pro vide further improvement.
基金Project(70631004)supported by the Key Project of the National Natural Science Foundation of ChinaProject(20080440988)supported by the Postdoctoral Science Foundation of China+1 种基金Project(09JJ4030)supported by the Natural Science Foundation of Hunan Province,ChinaProject supported by the Postdoctoral Science Foundation of Central South University,China
文摘Based on the deficiency of time convergence and variability of Web services selection for services composition supporting cross-enterprises collaboration,an algorithm QCDSS(QoS constraints of dynamic Web services selection)to resolve dynamic Web services selection with QoS global optimal path,was proposed.The essence of the algorithm was that the problem of dynamic Web services selection with QoS global optimal path was transformed into a multi-objective services composition optimization problem with QoS constraints.The operations of the cross and mutation in genetic algorithm were brought into PSOA(particle swarm optimization algorithm),forming an improved algorithm(IPSOA)to solve the QoS global optimal problem.Theoretical analysis and experimental results indicate that the algorithm can better satisfy the time convergence requirement for Web services composition supporting cross-enterprises collaboration than the traditional algorithms.
