Hierarchical multi-reservoir optimization modeling for real-world complexity with application to the Three Gorges system

High dimensionality in real-world multi-reservoir systems greatly hinders the application and popularity of evolutionary algorithms, especially for systems with heterogeneous units. An efficient hierarchical optimization framework is presented for search space reduction, determining the best water distributions, not only between cascade reservoirs, but also among different types of hydropower units. The framework is applied to the Three Gorges Project (TGP) system and the results demonstrate that the difficulties of multi-reservoir optimization caused by high dimensionality can be effectively solved by the proposed hierarchical method. For the day studied, power output could be increased by 6.79 GWh using an optimal decision with the same amount of water actually used; while the same amount of power could be generated with 2.59 × 10⁷ m³ less water compared to the historical policy. The methodology proposed is general in that it can be used for other reservoir systems and other types of heterogeneous unit generators.     

The robust knapsack problem with queries

We consider robust knapsack problems where item weights are uncertain. We are allowed to query an item to find its exact weight,where the number of such queries is bounded by a given parameter Q. After these queries are made, we need to pack the items robustly, i.e., so that the choice of items is feasible for every remaining possible scenario of item weights.The central question that we consider is: Which items should be queried in order to gain maximum profit? We introduce the notion of query competitiveness for strict robustness to evaluate the quality of an algorithm for this problem, and obtain lower and upper bounds on this competitiveness for interval-based uncertainty. Similar to the study of online algorithms, we study the competitiveness under different frameworks, namely we analyze the worst-case query competitiveness for deterministic algorithms, the expected query competitiveness for randomized algorithms and the average case competitiveness for known distributions of the uncertain input data. We derive theoretical bounds for these different frameworks and evaluate them experimentally. We also extend this approach to Γ-restricted uncertainties introduced by Bertsimas and Sim.Furthermore, we present heuristic algorithms for the problem. In computational experiments considering both the interval-based and the Γ-restricted uncertainty, we evaluate their empirical performance. While the usage of a Γ-restricted uncertainty improves the nominal performance of a solution (as expected), we find that the query competitiveness gets worse.     

ANN inverse analysis based on stochastic small-sample training set simulation

A new approach of inverse analysis is proposed to obtain parameters of a computational model in order to achieve the best agreement with experimental data. The inverse analysis is based on the coupling of a stochastic simulation and an artificial neural network (ANN). The identification parameters play the role of basic random variables with a scatter reflecting the physical range of potential values. A novelty of the approach is the utilization of the efficient small-sample simulation method Latin Hypercube Sampling (LHS) used for the stochastic preparation of the training set utilized in training the artificial neural network. Once the network has been trained, it represents an approximation consequently utilized to solve the key task: To provide the best possible set of model parameters for the given experimental data. The efficiency of the approach is shown using numerical examples from civil engineering computational mechanics.     

Zk线性码的对称形式的MacWilliams恒等式

该文定义了Zk线性码的码字的对称重量计数公式，利用离散的Hadamard变换，建立了线性码与其对偶码之间的对称形式的MacWilliams恒等式．     

连续小波变换在多元函数空问中的应用

使用连续小波变换讨论了某些偏微分方程和相应的积分方程之间的关系．使用连续小波变换能够将这些偏微分方程变换成相应的积分方程，这些偏微分方程与相应的积分方程不仅在弱收敛意义下是等价的，而且在范数收敛意义下也是等价的．     

An incremental primal sieve

Summary A new algorithm is presented for finding all primes between 2 and an incrementally increasing value n. The algorithm executes in linear arithmetic time and space. An outline is given to show how previously developed techniques can be applied to improve the efficiency of the algorithm to O(n/loglogn) time and space.     

Singular Trajectories in Multi-Input Time-Optimal Problems: Application to Controlled Mechanical Systems

This paper deals with the time-optimal control problem for a class of control systems which includes controlled mechanical systems with possible dissipation terms. The Lie algebras associated with such mechanical systems have certain special properties. These properties are explored and used in conjunction with the Pontryagin maximum principle to determine the structure of singular extremals and, in particular, time-optimal trajectories. The theory is illustrated by an application to a time-optimal problem for a class of underwater vehicles.     

Efficient use of route requests for loop-free on-demand routing in ad hoc networks

On-demand routing protocols flood a route request (RREQ) identified by a unique source-sequenced label (SSL) to build directed acyclic graphs (DAG) consisting of possible paths to destinations, and use reverse paths along such DAGs to send route replies from the destinations. We present the first framework that uses only the SSL of the RREQ to establish loop-free paths without requiring additional mechanisms or information, e.g., per destination-sequence numbers or source routing. We present the Labeled Successor Routing (LSR) protocol, which stores the SSL of the RREQ as a route request label (RRL) at the nodes that participated in the creation of the RREQ DAG. The RRLs allow the source of the RREQ to identify neighbors as loop-free successors to the destination, which reduces network-wide RREQ flooding. Simulations results for scenarios consisting of networks of 50 and 100 mobile nodes show that LSR performs comparably or better than the Dynamic Source Routing (DSR) protocol, the Ad hoc On-demand Distance Vector (AODV) routing protocol, and the Optimized Link State Routing (OLSR) protocol.     

Detecting delaminations in a composite beam using anti-optimization

The present study proposes a detection technique for delaminations in a laminated beam. The proposed technique optimizes the spatial distribution of harmonic excitation so as to magnify the difference in response between the delaminated and intact beam. The technique is evaluated by numerical simulation of two-layered aluminum beams. Effects of measurement and geometric noise are included in the analysis. A finite element model for a delaminated composite, based on a layer-wise laminated plate theory is used in conjunction with a step function to simulate delaminations