上海旅游产业化进程的发展路径和综合评价研究——一个基于经验分析的逻辑框架

本文用制度、旅游业宽度、产品线扩展等3个因素构成的"最优化空间"来解读上海旅游业改革开放30年的发展逻辑和路径,提出上海旅游业的发展是建立在制度变迁基础上的,而旅游业宽度和产品线扩展构成了推动上海旅游业发展的机制性结构,形成了上海旅游业不同发展阶段的模式,促使改革开放30年来上海旅游业从政府主导下"嵌入式"发展模式到规则性市场制度环境"产业推动型"发展模式的转变。

逐次逼近动态规划法求解水电机组组合问题

水电站厂内机组间的发电流量分配是水电站经济运行中的一个重要混合非线性优化问题。文章设计了一种逐次逼近动态规划法,可用于求解水电机组的组合问题。该算法可有效地减少状态变量的个数,且能收敛到满意解。通过实例研究,验证了模型合理性和算法的可行性与有效性。

An adaptive ant colony system algorithm for continuous-space optimization problems

Ant colony algorithms comprise a novel category of evolutionary computation methods for optimization problems, especially for sequencing-type combinatorial optimization problems. An adaptive ant colony algorithm is proposed in this paper to tackle continuous-space optimization problems, using a new objective-function-based heuristic pheromone assignment approach for pheromone update to filtrate solution candidates.Global optimal solutions can be reached more rapidly by self-adjusting the path searching behaviors of the ants according to objective values. The performance of the proposed algorithm is compared with a basic ant colony algorithm and a Square Quadratic Programming approach in solving two benchmark problems with multiple extremes. The results indicated that the efficiency and reliability of the proposed algorithm were greatly improved.

Optimal Initialization of a Quantum System for an Efficient Coherent Energy Transfer

For an energy transfer network, the irreversible depletion of excited electron energy occurs through either an efficient flow into an outer energy sink or an inefficient decay. With a small decay rate, the energy transfer efficiency is quantitatively reflected by the average life time of excitation energy before being trapped in the sink where the decay process is omitted. In the weak dissipation regime, the trapping time is analyzed within the exciton population subspace based on the secular Redfield equation. The requirement of the noise-enhanced energy transfer is obtained, where the trapping time follows an exact or approximate 1/F- scaling of the dissipation strength F. On the opposite side, optimal initial system states are conceptually constructed to suppress the 1/F-scaling of the trapping time and maximize the coherent transfer efficiency. Our theory is numerically testified in four models, including a biased two-site system, a symmetric three-site branching system, a homogeneous one- dimensional chain, and an 8-chromophore FMO protein complex.

AVERAGE σ-K WIDTH OF CLASS OF L_p(R^n) IN L_q (R^n)

The average σ-K width of the Sobolev-Wiener class in Lq(Rn) is studied for and the asymptotic behaviour of this quantity is determined. The exact value of average σ-K width of some class of smooth functions in L2(Rn) is obtained.

Analysis of Spatial Clustering Optimization

Spatial clustering is widely used in many fields such as WSN (Wireless Sensor Networks), web clustering, remote sensing and so on for discovery groups and to identify interesting distributions in the underlying database. By discussing the relationships between the optimal clustering and the initial seeds, a clustering validity index and the principle of seeking initial seeds were proposed, and on this principle we recommend an initial seed-seeking strategy: SSPG (Single-Shortest-Path Graph). With SSPG strategy used in clustering algorithms, we find that the result of clustering is optimized with more probability. At the end of the paper, according to the combinational theory of optimization, a method is proposed to obtain optimal reference k value of cluster number, and is proven to be efficient.

A TRUST REGION ALGORITHM WITH NULL SPACE TECHNIQUE FOR EQUALITY CONSTRAINED OPTIMIZATION

This paper presents a trust region algorithm with null space technique fornonlinear equality constrained optimization. Considering in the null space methods that,the convergent rate of range space step is faster than the null space step for the most cases,the proposed algorithm computes null steps more often than range space step. Moreover,the new algorithm is based on the reduced Hessian SQP method. Global convergence ofthe proposed algorithm is proved. The effectiveness of the method is demonstrated bysome numerical examples.

A Barzilai-Borwein conjugate gradient method

The linear conjugate gradient method is an optimal method for convex quadratic minimization due to the Krylov subspace minimization property. The proposition of limited-memory BFGS method and Barzilai-Borwein gradient method, however, heavily restricted the use of conjugate gradient method for largescale nonlinear optimization. This is, to the great extent, due to the requirement of a relatively exact line search at each iteration and the loss of conjugacy property of the search directions in various occasions. On the contrary, the limited-memory BFGS method and the Barzilai-Bowein gradient method share the so-called asymptotical one stepsize per line-search property, namely, the trial stepsize in the method will asymptotically be accepted by the line search when the iteration is close to the solution. This paper will focus on the analysis of the subspace minimization conjugate gradient method by Yuan and Stoer(1995). Specifically, if choosing the parameter in the method by combining the Barzilai-Borwein idea, we will be able to provide some efficient Barzilai-Borwein conjugate gradient(BBCG) methods. The initial numerical experiments show that one of the variants, BBCG3, is specially efficient among many others without line searches. This variant of the BBCG method might enjoy the asymptotical one stepsize per line-search property and become a strong candidate for large-scale nonlinear optimization.

Linear response eigenvalue problem solved by extended locally optimal preconditioned conjugate gradient methods

The locally optimal block preconditioned 4-d conjugate gradient method(LOBP4dC G) for the linear response eigenvalue problem was proposed by Bai and Li(2013) and later was extended to the generalized linear response eigenvalue problem by Bai and Li(2014). We put forward two improvements to the method: A shifting deflation technique and an idea of extending the search subspace. The deflation technique is able to deflate away converged eigenpairs from future computation, and the idea of extending the search subspace increases convergence rate per iterative step. The resulting algorithm is called the extended LOBP4 dC G(ELOBP4dC G).Numerical results of the ELOBP4 dC G strongly demonstrate the capability of deflation technique and effectiveness the search space extension for solving linear response eigenvalue problems arising from linear response analysis of two molecule systems.