Cooperative Optimization of Reconfigurable Machine Tool Configurations and Production Process Plan

The production process plan design and configurations of reconfigurable machine tool （RMT） interact with each other. Reasonable process plans with suitable configurations of RMT help to improve product quality and reduce production cost. Therefore, a cooperative strategy is needed to concurrently solve the above issue. In this paper, the cooperative optimization model for RMT configurations and production process plan is presented. Its objectives take into account both impacts of process and configuration. Moreover, a novel genetic algorithm is also developed to provide optimal or near-optimal solutions： firstly, its chromosome is redesigned which is composed of three parts, operations, process plan and configurations of RMTs, respectively; secondly, its new selection, crossover and mutation operators are also developed to deal with the process constraints from operation processes （OP） graph, otherwise these operators could generate illegal solutions violating the limits; eventually the optimal configurations for RMT under optimal process plan design can be obtained. At last, a manufacturing line case is applied which is composed of three RMTs. It is shown from the case that the optimal process plan and configurations of RMT are concurrently obtained, and the production cost decreases 6.28% and nonmonetary performance increases 22%. The proposed method can figure out both RMT configurations and production process, improve production capacity, functions and equipment utilization for RMT.

Service composition based on discrete particle swarm optimization in military organization cloud cooperation

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）.

Optimized Reimbursement Scheme of China's New Cooperative Medical System Using Monte Carlo Simulation

China＇s Rural Cooperative Medical System collapsed alongside communal farming at the end of the Maoist period in 1976, leaving most farmers vulnerable[1]. In rural areas, where 80% of people have been without health insurance of any kind, illness has emerged as a leading cause of poverty[24]. To address the poor state of health care among the rural population, in 2003 the Chinese government launched the New Rural Cooperative Medical System （NCMS）,

Optimization for PID Controller of Cryogenic Ground Support Equipment Based on Cooperative Random Learning Particle Swarm Optimization

Cryogenic ground support equipment (CGSE) is an important part of a famous particle physics experiment - AMS-02. In this paper a design method which optimizes PID parameters of CGSE control system via the particle swarm optimization (PSO) algorithm is presented. Firstly, an improved version of the original PSO, cooperative random learning particle swarm optimization (CRPSO), is put forward to enhance the performance of the conventional PSO. Secondly, the way of finding PID coefficient will be studied by using this algorithm. Finally, the experimental results and practical works demonstrate that the CRPSO-PID controller achieves a good performance.

A novel cooperative mid-course guidance scheme for multiple intercepting missiles

In the interception engagement,if the target movement information is not accurate enough for the mid-course guidance of intercepting missiles,the interception mission may fail as a result of large handover errors.This paper proposes a novel cooperative mid-course guidance scheme for multiple missiles to intercept a target under the condition of large detection errors.Under this scheme,the launch and interception moments are staggered for different missiles.The earlier launched missiles can obtain a relatively accurate detection to the target during their terminal guidance,based on which the latter missiles are permitted to eliminate the handover error in the mid-course guidance.A significant merit of this scheme is that the available resources are fully exploited and less missiles are needed to achieve the interception mission.To this end,first,the design of cooperative handover parameters is formulated as an optimization problem.Then,an algorithm based on Monte Carlo sampling and stochastic approximation is proposed to solve this optimization problem,and the convergence of the algorithm is proved as well.Finally,simulation experiments are carried out to validate the effectiveness of the proposed cooperative scheme and algorithm.

Applying Power Margin Tracking Droop Control to Flexible Operation in Multi-terminal DC Collector Systems of Renewable Generation

An emerging multi-terminal looped DC(MTDC)collector system is now advocated for collecting and transferring large-scale renewable generation.However,it remains an open question as to improving the cooperative control capability of looped converter stations for flexible and robust response to renewable grid-connection fluctuation.This paper addresses this problem with a novel Power Margin Tracking(PMT)droop control and its corresponding system-level control strategy from the perspective of optimal dispatch of the power system.By introducing a power margin correction factor into the droop coefficient,the converter station can make self-adaptive regulations according to its actual available power margin.For operation verification,a multi-period optimal operation model and a four-terminal simulation model is built to provide optimal control parameters and real-time operation states of converter stations,where the power flow model of the looped MTDC grid with renewables generation is considered.The case results prove that the proposed control strategy can improve the cooperative operation capability of multiple converter stations,mitigating grid-connected power fluctuation.It can effectively reduce the DC voltage deviation to enhance the operation stability of the MTDC grid.The operational robustness of the proposed control strategy under“N−1”fault cases is verified as well.