In this paper, it is supposed that the B&B algorithm finds the first optimal solution after h nodes have been expanded and m active nodes have been created in the state-space tree. Then the lower bound Ω(m+h log ...In this paper, it is supposed that the B&B algorithm finds the first optimal solution after h nodes have been expanded and m active nodes have been created in the state-space tree. Then the lower bound Ω(m+h log h) of the running time for the general sequential B&B algorithm and the lower bound Ω(m/p+h log p) for the general parallel best-first B&B algorithm in PRAM-CREW are proposed, where p is the number of processors available. Moreover, the lower bound Ω(M/p+H+(H/p) log (H/p)) is presented for the parallel algorithms on distributed memory system, where M and H represent total number of the active nodes and that of the expanded nodes processed by p processors, respectively. In addition, a nearly fastest general parallel best-first B&B algorithm is put forward. The parallel algorithm is the fastest one as p = max{hε, r}, where ε = 1/ rootlogh, and r is the largest branch number of the nodes in the state-space tree.展开更多
In this paper a class of real-time parallel modified Rosenbrock methods of numerical simulation is constructed for stiff dynamic systems on a multiprocessor system, and convergence and numerical stability of these met...In this paper a class of real-time parallel modified Rosenbrock methods of numerical simulation is constructed for stiff dynamic systems on a multiprocessor system, and convergence and numerical stability of these methods are discussed. A-stable real-time parallel formula of two-stage third-order and A(α)-stable real-time parallel formula with o ≈ 89.96° of three-stage fourth-order are particularly given. The numerical simulation experiments in parallel environment show that the class of algorithms is efficient and applicable, with greater speedup.展开更多
Considering premature convergence in the searching process of genetic algorithm, a chaotic migration-based pseudo parallel genetic algorithm (CMPPGA) is proposed, which applies the idea of isolated evolution and infor...Considering premature convergence in the searching process of genetic algorithm, a chaotic migration-based pseudo parallel genetic algorithm (CMPPGA) is proposed, which applies the idea of isolated evolution and information exchanging in distributed Parallel Genetic Algorithm by serial program structure to solve optimization problem of low real-time demand. In this algorithm, asynchronic migration of individuals during parallel evolution is guided by a chaotic migration sequence. Information exchanging among sub-populations is ensured to be efficient and sufficient due to that the sequence is ergodic and stochastic. Simulation study of CMPPGA shows its strong global search ability, superiority to standard genetic algorithm and high immunity against premature convergence. According to the practice of raw material supply, an inventory programming model is set up and solved by CMPPGA with satisfactory results returned.展开更多
The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this wor...The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this work, a novel mathematic model for the hybrid flow shop scheduling problem with unrelated parallel machine(HFSPUPM) was proposed. Additionally, an effective hybrid estimation of distribution algorithm was proposed to solve the HFSPUPM, taking advantage of the features in the mathematic model. In the optimization algorithm, a new individual representation method was adopted. The(EDA) structure was used for global search while the teaching learning based optimization(TLBO) strategy was used for local search. Based on the structure of the HFSPUPM, this work presents a series of discrete operations. Simulation results show the effectiveness of the proposed hybrid algorithm compared with other algorithms.展开更多
As a typical representative of the NP-complete problem, the traveling salesman problem(TSP) is widely utilized in computer networks, logistics distribution, and other fields. In this paper, a discrete lion swarm optim...As a typical representative of the NP-complete problem, the traveling salesman problem(TSP) is widely utilized in computer networks, logistics distribution, and other fields. In this paper, a discrete lion swarm optimization(DLSO) algorithm is proposed to solve the TSP. Firstly, we introduce discrete coding and order crossover operators in DLSO. Secondly, we use the complete 2-opt(C2-opt) algorithm to enhance the local search ability.Then in order to enhance the efficiency of the algorithm, a parallel discrete lion swarm optimization(PDLSO) algorithm is proposed.The PDLSO has multiple populations, and each sub-population independently runs the DLSO algorithm in parallel. We use the ring topology to transfer information between sub-populations. Experiments on some benchmarks TSP problems show that the DLSO algorithm has a better accuracy than other algorithms, and the PDLSO algorithm can effectively shorten the running time.展开更多
For a large-scale adaptive array, the heavy computational load and the high-rate data transmission are two challenges in the implementation of an adaptive digital beamforming system. An efficient parallel digital beam...For a large-scale adaptive array, the heavy computational load and the high-rate data transmission are two challenges in the implementation of an adaptive digital beamforming system. An efficient parallel digital beamforming （DBF） algorithm based on the least mean square algorithm （PLMS） is proposed. An appropriate method is found to partition the least mean square （LMS） algorithm into a number of operational modules, which can be easily executed in a distributed-parallel-processing fashion. As a result, the proposed PLMS algorithm provides an effective solution that can alleviate the bottleneck of high-rate data transmission and reduce the computational cost. PLMS requires less computational load than that of the conventional parallel algorithms based on the recursive least square （RLS） algorithm, as well as it is easier to be implemented to do real time adaptive array processing. Moreover, low sidelobe of the beam pattern is obtained by constraining the static steering vector with Tschebyscheff coefficients. Finally, a scheme of the PLMS algorithm using distributed-parallel-processing system is also proposed. The simulation results demonstrate that the PLMS algorithm has the same interference cancellation performance as that of the conventional LMS algorithm. Moreover, the PLMS algorithm can obtain the same good beamforming performance, regardless how the algorithm is partitioned. It is expected that the proposed algorithm will be used in a large-scale adaptive array system to deal with real time adaptive digital beamforming processing.展开更多
In this paper, a parallel simulation algorithm for the control problem in differential algebraic system is presented. The error of the algorithm is estimated. The stability analysis is made for a model problem and the...In this paper, a parallel simulation algorithm for the control problem in differential algebraic system is presented. The error of the algorithm is estimated. The stability analysis is made for a model problem and the stability region is given. The numerical example demonstrates that the method is efficient.展开更多
With the new development trend of multi-resource coordinated Earth observation and the new goal of Earth observation application of“short response time,high observation accuracy,and wide coverage”,space-aeronautics ...With the new development trend of multi-resource coordinated Earth observation and the new goal of Earth observation application of“short response time,high observation accuracy,and wide coverage”,space-aeronautics cooperative complex task planning problem has become an urgent problem to be solved.The focus of this problem is to use multiple resources to perform collaborative observations on complex tasks.By analyzing the process from task assignment to receiving task observation results,we propose a multi-layer interactive task planning framework which is composed of a preprocessing method for complex tasks,a task allocation layer,a task planning layer,and a task coordination layer.According to the characteristics of the framework,a hybrid genetic parallel tabu(HGPT)algorithm is proposed on this basis.The algorithm uses genetic annealing algorithm(GAA),parallel tabu(PT)algorithm,and heuristic rules to achieve task allocation,task planning,and task coordination.At the same time,coding improvements,operator design,annealing operations,and parallel calculations are added to the algorithm.In order to verify the effectiveness of the algorithm,simulation experiments under complex task scenarios of different scales are carried out.Experimental results show that this method can effectively solve the problems of observing complex tasks.Meanwhile,the optimization effect and convergence speed of the HGPT is better than that of the related algorithms.展开更多
Milling Process Simulation is one of the important re search areas in manufacturing science. For the purpose of improving the prec ision of simulation and extending its usability, numerical algorithm is more and more ...Milling Process Simulation is one of the important re search areas in manufacturing science. For the purpose of improving the prec ision of simulation and extending its usability, numerical algorithm is more and more used in the milling modeling areas. But simulative efficiency is decreasin g with increase of its complexity. As a result, application of the method is lim ited. Aimed at above question, high-efficient algorithm for milling process sim ulation is studied. It is important for milling process simulation’s applicatio n. Parallel computing is widely used to solve the large-scale computation question s. Its advantages include system flexibility, robust, high-efficient computing capability and high ratio of performance to price. With the development of compu ter network, utilizing the computing resource in the Internet, a virtual computi ng environment with powerful computing capability can be consisted by microc omputers, and the difficulty of building hardware environment which is used to s upport parallel computing is reduced. How to use network technology and parallel algorithm to improve simulative effic iency for milling forces simulation is investigated in the paper. In order to pr edict milling forces, a simplified local milling forces model is used in the pap er. End milling cutter is assumed to be divided by r number of differential elem ents along the axial direction of the cutter. For a given time, the total cuttin g forces can be obtained by summarizing the resultant cutting force produced by each differential cutter disc. Divide the whole simulative time into some segmen ts, send these program’s segments to microcomputers in the Internet and obtain the result of the program’s segments, all of the result of program’s segments a re composed the final result. For implementing the algorithm, a distributed Parallel computing framework is de signed in the paper. In the framework, web server plays a role of controller. Us ing Java RMI(remote method interface), the computing processes in computing serv er are called by web server. There are lots of control processes in web server a nd control the computing servers. The codes of simulative algorithm can be dynam ic sent to the computing servers, and milling forces at the different time are c omputed through utilizing the local computer’s resource. The results that are ca lculated by every computing servers are sent to the web server, and composed the final result. The framework can be used by different simulative algorithm. Comp ared with the algorithm running single machine, the efficiency of provided algor ithm is higher than that of single machine.展开更多
In this paper, the stability analysis for parallel real-time digital simulation models is discussed. The coupling coefficient perturbation method and the simulation stepsize perturbation method are established. For tw...In this paper, the stability analysis for parallel real-time digital simulation models is discussed. The coupling coefficient perturbation method and the simulation stepsize perturbation method are established. For two classes of systems of test equations, we construct the parallel simulation models and prove that they have the stability behaviour which is similar to the original continuous systems.展开更多
A class of parallel implicit Runge-Kutta formulas is constructed for multiprocessor system. A family of parallel implicit two-stage fourth order Runge-Kutta formulas is given. For these formulas, the convergence is pr...A class of parallel implicit Runge-Kutta formulas is constructed for multiprocessor system. A family of parallel implicit two-stage fourth order Runge-Kutta formulas is given. For these formulas, the convergence is proved and the stability analysis is given. The numerical examples demonstrate that these formulas can solve an extensive class of initial value problems for the ordinary differential equations.展开更多
Parallel versions of prestack KirchhofT 3D integral migration algorithm, which is suitable forseismic data processing, are described in this paper. Firstly, the inherent parallel characteristics of seismicdata process...Parallel versions of prestack KirchhofT 3D integral migration algorithm, which is suitable forseismic data processing, are described in this paper. Firstly, the inherent parallel characteristics of seismicdata processing are analyzed. Then some principles in algorithm partition are discussed. Based on these analyses and the system architecture, communication mechanism, this algorithm is divided into four subtasksallocated to four nodes of 990 STAR-l. Then we describe in detail a module-partitioning method-theI / O processing and communication are separated from the computation process, the processes includingI / O processing and communication are allocated to transputer T805 and the other is allocated to processori860. These two processes are synchronized by shared memory and memory-lock mechanism, but the communication betWeen different nodes is implemented through links of transputer. Load balance among fourprocessor modules is performed dynamically. Finally, we discussed the speed--up of the parallel versions ofprestack KirchhofT 3D integral migration algorithm running on four nodes. Some further researches are also melltioned in this paper.展开更多
基金This paper was supported by Ph. D. Foundation of State Education Commission of China.
文摘In this paper, it is supposed that the B&B algorithm finds the first optimal solution after h nodes have been expanded and m active nodes have been created in the state-space tree. Then the lower bound Ω(m+h log h) of the running time for the general sequential B&B algorithm and the lower bound Ω(m/p+h log p) for the general parallel best-first B&B algorithm in PRAM-CREW are proposed, where p is the number of processors available. Moreover, the lower bound Ω(M/p+H+(H/p) log (H/p)) is presented for the parallel algorithms on distributed memory system, where M and H represent total number of the active nodes and that of the expanded nodes processed by p processors, respectively. In addition, a nearly fastest general parallel best-first B&B algorithm is put forward. The parallel algorithm is the fastest one as p = max{hε, r}, where ε = 1/ rootlogh, and r is the largest branch number of the nodes in the state-space tree.
基金This project was supported by the National Natural Science Foundation of China (No. 19871080).
文摘In this paper a class of real-time parallel modified Rosenbrock methods of numerical simulation is constructed for stiff dynamic systems on a multiprocessor system, and convergence and numerical stability of these methods are discussed. A-stable real-time parallel formula of two-stage third-order and A(α)-stable real-time parallel formula with o ≈ 89.96° of three-stage fourth-order are particularly given. The numerical simulation experiments in parallel environment show that the class of algorithms is efficient and applicable, with greater speedup.
文摘Considering premature convergence in the searching process of genetic algorithm, a chaotic migration-based pseudo parallel genetic algorithm (CMPPGA) is proposed, which applies the idea of isolated evolution and information exchanging in distributed Parallel Genetic Algorithm by serial program structure to solve optimization problem of low real-time demand. In this algorithm, asynchronic migration of individuals during parallel evolution is guided by a chaotic migration sequence. Information exchanging among sub-populations is ensured to be efficient and sufficient due to that the sequence is ergodic and stochastic. Simulation study of CMPPGA shows its strong global search ability, superiority to standard genetic algorithm and high immunity against premature convergence. According to the practice of raw material supply, an inventory programming model is set up and solved by CMPPGA with satisfactory results returned.
基金Projects(61573144,61773165,61673175,61174040)supported by the National Natural Science Foundation of ChinaProject(222201717006)supported by the Fundamental Research Funds for the Central Universities,China
文摘The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this work, a novel mathematic model for the hybrid flow shop scheduling problem with unrelated parallel machine(HFSPUPM) was proposed. Additionally, an effective hybrid estimation of distribution algorithm was proposed to solve the HFSPUPM, taking advantage of the features in the mathematic model. In the optimization algorithm, a new individual representation method was adopted. The(EDA) structure was used for global search while the teaching learning based optimization(TLBO) strategy was used for local search. Based on the structure of the HFSPUPM, this work presents a series of discrete operations. Simulation results show the effectiveness of the proposed hybrid algorithm compared with other algorithms.
基金supported by the National Natural Science Foundation of China(61771293)the Key Project of Shangdong Province(2019JZZY010111)。
文摘As a typical representative of the NP-complete problem, the traveling salesman problem(TSP) is widely utilized in computer networks, logistics distribution, and other fields. In this paper, a discrete lion swarm optimization(DLSO) algorithm is proposed to solve the TSP. Firstly, we introduce discrete coding and order crossover operators in DLSO. Secondly, we use the complete 2-opt(C2-opt) algorithm to enhance the local search ability.Then in order to enhance the efficiency of the algorithm, a parallel discrete lion swarm optimization(PDLSO) algorithm is proposed.The PDLSO has multiple populations, and each sub-population independently runs the DLSO algorithm in parallel. We use the ring topology to transfer information between sub-populations. Experiments on some benchmarks TSP problems show that the DLSO algorithm has a better accuracy than other algorithms, and the PDLSO algorithm can effectively shorten the running time.
文摘For a large-scale adaptive array, the heavy computational load and the high-rate data transmission are two challenges in the implementation of an adaptive digital beamforming system. An efficient parallel digital beamforming （DBF） algorithm based on the least mean square algorithm （PLMS） is proposed. An appropriate method is found to partition the least mean square （LMS） algorithm into a number of operational modules, which can be easily executed in a distributed-parallel-processing fashion. As a result, the proposed PLMS algorithm provides an effective solution that can alleviate the bottleneck of high-rate data transmission and reduce the computational cost. PLMS requires less computational load than that of the conventional parallel algorithms based on the recursive least square （RLS） algorithm, as well as it is easier to be implemented to do real time adaptive array processing. Moreover, low sidelobe of the beam pattern is obtained by constraining the static steering vector with Tschebyscheff coefficients. Finally, a scheme of the PLMS algorithm using distributed-parallel-processing system is also proposed. The simulation results demonstrate that the PLMS algorithm has the same interference cancellation performance as that of the conventional LMS algorithm. Moreover, the PLMS algorithm can obtain the same good beamforming performance, regardless how the algorithm is partitioned. It is expected that the proposed algorithm will be used in a large-scale adaptive array system to deal with real time adaptive digital beamforming processing.
文摘In this paper, a parallel simulation algorithm for the control problem in differential algebraic system is presented. The error of the algorithm is estimated. The stability analysis is made for a model problem and the stability region is given. The numerical example demonstrates that the method is efficient.
基金the National Natural Science Foundation of China(72001212).
文摘With the new development trend of multi-resource coordinated Earth observation and the new goal of Earth observation application of“short response time,high observation accuracy,and wide coverage”,space-aeronautics cooperative complex task planning problem has become an urgent problem to be solved.The focus of this problem is to use multiple resources to perform collaborative observations on complex tasks.By analyzing the process from task assignment to receiving task observation results,we propose a multi-layer interactive task planning framework which is composed of a preprocessing method for complex tasks,a task allocation layer,a task planning layer,and a task coordination layer.According to the characteristics of the framework,a hybrid genetic parallel tabu(HGPT)algorithm is proposed on this basis.The algorithm uses genetic annealing algorithm(GAA),parallel tabu(PT)algorithm,and heuristic rules to achieve task allocation,task planning,and task coordination.At the same time,coding improvements,operator design,annealing operations,and parallel calculations are added to the algorithm.In order to verify the effectiveness of the algorithm,simulation experiments under complex task scenarios of different scales are carried out.Experimental results show that this method can effectively solve the problems of observing complex tasks.Meanwhile,the optimization effect and convergence speed of the HGPT is better than that of the related algorithms.
文摘Milling Process Simulation is one of the important re search areas in manufacturing science. For the purpose of improving the prec ision of simulation and extending its usability, numerical algorithm is more and more used in the milling modeling areas. But simulative efficiency is decreasin g with increase of its complexity. As a result, application of the method is lim ited. Aimed at above question, high-efficient algorithm for milling process sim ulation is studied. It is important for milling process simulation’s applicatio n. Parallel computing is widely used to solve the large-scale computation question s. Its advantages include system flexibility, robust, high-efficient computing capability and high ratio of performance to price. With the development of compu ter network, utilizing the computing resource in the Internet, a virtual computi ng environment with powerful computing capability can be consisted by microc omputers, and the difficulty of building hardware environment which is used to s upport parallel computing is reduced. How to use network technology and parallel algorithm to improve simulative effic iency for milling forces simulation is investigated in the paper. In order to pr edict milling forces, a simplified local milling forces model is used in the pap er. End milling cutter is assumed to be divided by r number of differential elem ents along the axial direction of the cutter. For a given time, the total cuttin g forces can be obtained by summarizing the resultant cutting force produced by each differential cutter disc. Divide the whole simulative time into some segmen ts, send these program’s segments to microcomputers in the Internet and obtain the result of the program’s segments, all of the result of program’s segments a re composed the final result. For implementing the algorithm, a distributed Parallel computing framework is de signed in the paper. In the framework, web server plays a role of controller. Us ing Java RMI(remote method interface), the computing processes in computing serv er are called by web server. There are lots of control processes in web server a nd control the computing servers. The codes of simulative algorithm can be dynam ic sent to the computing servers, and milling forces at the different time are c omputed through utilizing the local computer’s resource. The results that are ca lculated by every computing servers are sent to the web server, and composed the final result. The framework can be used by different simulative algorithm. Comp ared with the algorithm running single machine, the efficiency of provided algor ithm is higher than that of single machine.
基金This work is supported partly by the National Natural Science Foundation of China
文摘In this paper, the stability analysis for parallel real-time digital simulation models is discussed. The coupling coefficient perturbation method and the simulation stepsize perturbation method are established. For two classes of systems of test equations, we construct the parallel simulation models and prove that they have the stability behaviour which is similar to the original continuous systems.
基金Project supported by the National Natural Science Foundation of China
文摘A class of parallel implicit Runge-Kutta formulas is constructed for multiprocessor system. A family of parallel implicit two-stage fourth order Runge-Kutta formulas is given. For these formulas, the convergence is proved and the stability analysis is given. The numerical examples demonstrate that these formulas can solve an extensive class of initial value problems for the ordinary differential equations.
文摘Parallel versions of prestack KirchhofT 3D integral migration algorithm, which is suitable forseismic data processing, are described in this paper. Firstly, the inherent parallel characteristics of seismicdata processing are analyzed. Then some principles in algorithm partition are discussed. Based on these analyses and the system architecture, communication mechanism, this algorithm is divided into four subtasksallocated to four nodes of 990 STAR-l. Then we describe in detail a module-partitioning method-theI / O processing and communication are separated from the computation process, the processes includingI / O processing and communication are allocated to transputer T805 and the other is allocated to processori860. These two processes are synchronized by shared memory and memory-lock mechanism, but the communication betWeen different nodes is implemented through links of transputer. Load balance among fourprocessor modules is performed dynamically. Finally, we discussed the speed--up of the parallel versions ofprestack KirchhofT 3D integral migration algorithm running on four nodes. Some further researches are also melltioned in this paper.
