This paper proposes an optimized simulated annealing(SA) algorithm for thinning and weighting large planar arrays in 3D underwater sonar imaging systems.The optimized algorithm has been developed for use in designing ...This paper proposes an optimized simulated annealing(SA) algorithm for thinning and weighting large planar arrays in 3D underwater sonar imaging systems.The optimized algorithm has been developed for use in designing a 2D planar array(a rectangular grid with a circular boundary) with a fixed side-lobe peak and a fixed current taper ratio under a narrow-band excitation.Four extensions of the SA algorithm and the procedure for the optimized SA algorithm are described.Two examples of planar arrays are used to assess the efficiency of the optimized method.The proposed method achieves a similar beam pattern performance with fewer active transducers and faster convergence ability than previous SA algorithms.展开更多
We propose a method for estimating the mutual coupling coefficient among antennas in this paper which is based on the principle of signal subspace and the simulated annealing （SA） algorithm. The computer simulation ...We propose a method for estimating the mutual coupling coefficient among antennas in this paper which is based on the principle of signal subspace and the simulated annealing （SA） algorithm. The computer simulation has been conducted to illustrate the＇ excellent performance of this method and to demonstrate that it is statistically efficient. The benefit of this new method is that calibration signals and unknown signals can be received simultaneously, during the course of calibration.展开更多
Binary code signals have been widely used in various radars due to their simpleimplementation,but the selection of the binary codes with high comporession ratio and lowsidelobes is not solved well,because of the diffi...Binary code signals have been widely used in various radars due to their simpleimplementation,but the selection of the binary codes with high comporession ratio and lowsidelobes is not solved well,because of the difficult processing in mathmatics and expensivecalculation cost.In this paper,neural computing is introduced into the field of the selection ofbinary codes and a new method based’on simulated annealing(SA)is proposed.The experimentsshow that the proposed method is able to select the optimal binary codes with much less timecost than the known methods,furhtermore the optimization selection of the binary codes versusthe calculation cost tradeoff is easier.展开更多
An economic dispatch problem for power system with wind power is discussed.Using discrete scenario to describe uncertain wind powers,a threshold is given to identify bad scenario set.The bad-scenario-set robust econom...An economic dispatch problem for power system with wind power is discussed.Using discrete scenario to describe uncertain wind powers,a threshold is given to identify bad scenario set.The bad-scenario-set robust economic dispatch model is established to minimize the total penalties on bad scenarios.A specialized hybrid particle swarm optimization(PSO)algorithm is developed through hybridizing simulated annealing(SA)operators.The SA operators are performed according to a scenario-oriented adaptive search rule in a neighborhood which is constructed based on the unit commitment constraints.Finally,an experiment is conducted.The computational results show that the developed algorithm outperforms the existing algorithms.展开更多
Multi-constrained quality of service(QoS)routing aims at finding an optimal path that satisfies a set of QoS parameters,as an NP complete problem,which is also a big challenge for wireless mesh networks(WMNs).Heuristi...Multi-constrained quality of service(QoS)routing aims at finding an optimal path that satisfies a set of QoS parameters,as an NP complete problem,which is also a big challenge for wireless mesh networks(WMNs).Heuristic algorithms with polynomial and pseudo-polynomial-time complexities are often used to deal with this problem.However,existing solutions,most of which suffered either from excessive computational complexities or from low performance,were proposed only for wired networks and cannot be used directly in wireless mesh networks.In this paper,we propose a novel routing scheme based on mean field annealing(MFA-RS)to solve this problem.MFA-RS first uses a function of two QoS parameters,wireless link’s delay and transmission success rate as the cost function,and then seeks to find a feasible path by MFA.Because MFA-RS uses a set of deterministic equations to replace the stochastic process in simulated annealing(SA)and uses saddle point approximation in the calculation of the stationary probability distribution at equilibrium,the convergence time is much less than the routing scheme based on SA(SA-RS).Simulation results demonstrate that MFA-RS is an effective algorithm and is very fit for WMNs.展开更多
Design for six sigma （DFSS） is a powerful approach of designing products, processes, and services with the objective of meeting the needs of customers in a cost-effective maimer. DFSS activities are classified into ...Design for six sigma （DFSS） is a powerful approach of designing products, processes, and services with the objective of meeting the needs of customers in a cost-effective maimer. DFSS activities are classified into four major phases viz. identify, design, optimize, and validate （IDOV）. And an adaptive design for six sigma （ADFSS） incorporating the traits of artifidai intelligence and statistical techniques is presented. In the identify phase of the ADFSS, fuzzy relation measures between customer attributes （CAs） and engineering characteristics （ECs） as well as fuzzy correlation measures among ECs are determined with the aid of two fuzzy logic controllers （FLCs）. These two measures are then used to establish the cumulative impact factor for ECs. In the next phase （ i. e. design phase）, a transfer function is developed with the aid of robust multiple nonlinear regression analysis. Furthermore, 1this transfer function is optimized with the simulated annealing （ SA ） algorithm in the optimize phase. In the validate phase, t-test is conducted for the validation of the design resulted in earlier phase. Finally, a case study of a hypothetical writing instrument is simulated to test the efficacy of the proposed ADFSS.展开更多
Optical networks act as a backbone for coming generation high speed applications.These applications demand a very high bandwidth which can be exploited with the use of wavelength division multiplexing(WDM)technology.T...Optical networks act as a backbone for coming generation high speed applications.These applications demand a very high bandwidth which can be exploited with the use of wavelength division multiplexing(WDM)technology.The issue of setting light paths for the traffic demands is routing and wavelength assignment(RWA)problem.Based on the type of traffic patterns,it can be categorized as offline or online RWA.In this paper,an effective solution to offline(static)routing and wavelength assignment is presented considering multiple objectives simultaneously.Initially,the flower pollination(FP)technique is utilized.Then the problem is extended with the parallel hybrid technique with flower pollination and intelligent water drop algorithm(FPIWDA).Further,FPIWD is hybrid in parallel with simulated annealing(SA)algorithm to propose a parallel hybrid algorithm FPIWDSA.The results obtained through extensive simulation show the superiority of FPIWD as compared to FP.Moreover,the results in terms of blocking probability with respect to wavelengths and load of FPIWDSA are more propitious than FP and FPIWD.展开更多
This paper presents a comparative study of evolutionary algorithms which are considered to be effective in solving the multilevel lot-sizing problem in material requirement planning(MRP)systems.Three evolutionary algo...This paper presents a comparative study of evolutionary algorithms which are considered to be effective in solving the multilevel lot-sizing problem in material requirement planning(MRP)systems.Three evolutionary algorithms(simulated annealing(SA),particle swarm optimization(PSO)and genetic algorithm(GA))are provided.For evaluating the performances of algorithms,the distribution of total cost(objective function)and the average computational time are compared.As a result,both GA and PSO have better cost performances with lower average total costs and smaller standard deviations.When the scale of the multilevel lot-sizing problem becomes larger,PSO is of a shorter computational time.展开更多
基金Project (No.2006AA09Z109) supported by the National High-Tech Research and Development Program (863) of China
文摘This paper proposes an optimized simulated annealing(SA) algorithm for thinning and weighting large planar arrays in 3D underwater sonar imaging systems.The optimized algorithm has been developed for use in designing a 2D planar array(a rectangular grid with a circular boundary) with a fixed side-lobe peak and a fixed current taper ratio under a narrow-band excitation.Four extensions of the SA algorithm and the procedure for the optimized SA algorithm are described.Two examples of planar arrays are used to assess the efficiency of the optimized method.The proposed method achieves a similar beam pattern performance with fewer active transducers and faster convergence ability than previous SA algorithms.
基金Supported by the 863 High Technology Project ofChina (2001AA631050)
文摘We propose a method for estimating the mutual coupling coefficient among antennas in this paper which is based on the principle of signal subspace and the simulated annealing （SA） algorithm. The computer simulation has been conducted to illustrate the＇ excellent performance of this method and to demonstrate that it is statistically efficient. The benefit of this new method is that calibration signals and unknown signals can be received simultaneously, during the course of calibration.
文摘Binary code signals have been widely used in various radars due to their simpleimplementation,but the selection of the binary codes with high comporession ratio and lowsidelobes is not solved well,because of the difficult processing in mathmatics and expensivecalculation cost.In this paper,neural computing is introduced into the field of the selection ofbinary codes and a new method based’on simulated annealing(SA)is proposed.The experimentsshow that the proposed method is able to select the optimal binary codes with much less timecost than the known methods,furhtermore the optimization selection of the binary codes versusthe calculation cost tradeoff is easier.
基金supported by the National Natural Science Foundation of China(62173219,62073210).
文摘An economic dispatch problem for power system with wind power is discussed.Using discrete scenario to describe uncertain wind powers,a threshold is given to identify bad scenario set.The bad-scenario-set robust economic dispatch model is established to minimize the total penalties on bad scenarios.A specialized hybrid particle swarm optimization(PSO)algorithm is developed through hybridizing simulated annealing(SA)operators.The SA operators are performed according to a scenario-oriented adaptive search rule in a neighborhood which is constructed based on the unit commitment constraints.Finally,an experiment is conducted.The computational results show that the developed algorithm outperforms the existing algorithms.
基金supported by the National Natural Science Foundation of China(Grant Nos.61002016 and 60702081)the Natural Science Foundation of Zhejiang Province of China(No.Y107309)+2 种基金the University Scientific Research Program of the Education Department of Zhejiang Province of China(No.20070364)the Scientific Research Foundation of Zhejiang Sci-Tech University(Nos.0704698 and 0704697)the Xinmiao Talent Project of Zhejiang Province(2009).
文摘Multi-constrained quality of service(QoS)routing aims at finding an optimal path that satisfies a set of QoS parameters,as an NP complete problem,which is also a big challenge for wireless mesh networks(WMNs).Heuristic algorithms with polynomial and pseudo-polynomial-time complexities are often used to deal with this problem.However,existing solutions,most of which suffered either from excessive computational complexities or from low performance,were proposed only for wired networks and cannot be used directly in wireless mesh networks.In this paper,we propose a novel routing scheme based on mean field annealing(MFA-RS)to solve this problem.MFA-RS first uses a function of two QoS parameters,wireless link’s delay and transmission success rate as the cost function,and then seeks to find a feasible path by MFA.Because MFA-RS uses a set of deterministic equations to replace the stochastic process in simulated annealing(SA)and uses saddle point approximation in the calculation of the stationary probability distribution at equilibrium,the convergence time is much less than the routing scheme based on SA(SA-RS).Simulation results demonstrate that MFA-RS is an effective algorithm and is very fit for WMNs.
基金Shanghai Leading Academic Discipline Project,China(No.B602)
文摘Design for six sigma （DFSS） is a powerful approach of designing products, processes, and services with the objective of meeting the needs of customers in a cost-effective maimer. DFSS activities are classified into four major phases viz. identify, design, optimize, and validate （IDOV）. And an adaptive design for six sigma （ADFSS） incorporating the traits of artifidai intelligence and statistical techniques is presented. In the identify phase of the ADFSS, fuzzy relation measures between customer attributes （CAs） and engineering characteristics （ECs） as well as fuzzy correlation measures among ECs are determined with the aid of two fuzzy logic controllers （FLCs）. These two measures are then used to establish the cumulative impact factor for ECs. In the next phase （ i. e. design phase）, a transfer function is developed with the aid of robust multiple nonlinear regression analysis. Furthermore, 1this transfer function is optimized with the simulated annealing （ SA ） algorithm in the optimize phase. In the validate phase, t-test is conducted for the validation of the design resulted in earlier phase. Finally, a case study of a hypothetical writing instrument is simulated to test the efficacy of the proposed ADFSS.
文摘Optical networks act as a backbone for coming generation high speed applications.These applications demand a very high bandwidth which can be exploited with the use of wavelength division multiplexing(WDM)technology.The issue of setting light paths for the traffic demands is routing and wavelength assignment(RWA)problem.Based on the type of traffic patterns,it can be categorized as offline or online RWA.In this paper,an effective solution to offline(static)routing and wavelength assignment is presented considering multiple objectives simultaneously.Initially,the flower pollination(FP)technique is utilized.Then the problem is extended with the parallel hybrid technique with flower pollination and intelligent water drop algorithm(FPIWDA).Further,FPIWD is hybrid in parallel with simulated annealing(SA)algorithm to propose a parallel hybrid algorithm FPIWDSA.The results obtained through extensive simulation show the superiority of FPIWD as compared to FP.Moreover,the results in terms of blocking probability with respect to wavelengths and load of FPIWDSA are more propitious than FP and FPIWD.
基金the National Natural Science Foundation of China(No.70971017)the Humanities and Social Sciences Project of Ministry of Education(No.10YJC630009)+1 种基金the Social Science Fund of Zhejiang Province(No.10CGGL21YBQ)the Natural Science Foundation of Zhejiang Province(No.Y1100854)
文摘This paper presents a comparative study of evolutionary algorithms which are considered to be effective in solving the multilevel lot-sizing problem in material requirement planning(MRP)systems.Three evolutionary algorithms(simulated annealing(SA),particle swarm optimization(PSO)and genetic algorithm(GA))are provided.For evaluating the performances of algorithms,the distribution of total cost(objective function)and the average computational time are compared.As a result,both GA and PSO have better cost performances with lower average total costs and smaller standard deviations.When the scale of the multilevel lot-sizing problem becomes larger,PSO is of a shorter computational time.
