多盘失效的可修复RAID系统的可靠性分析

本文对多盘失效的可修复ＲＡＩＤ系统的可靠性进行了分析和讨论，并给出了多盘失效的可修复ＲＡＩＤ系统的ＭＴＴＦ的计算公式。     

多媒体PC中声音信息的文件格式

本文介绍了ＲＩＦＦ文件格式的一般定义，在此基础上对多媒体ＰＣ（ＭＰＣ）中的声音信息文件格式进行剖析，详细分析了两种ＲＩＦＦ文件格式（ＷＡＶＥ、ＲＭＩＤ）和标准ＭＩＤＩ文件格式的结构。     

模型参考自适应控制,模糊控制及PID控制的综合应用

模型参考自适应控制、模糊控制及ＰＩＤ控制的综合应用ＴｈｅＣｏｍｐｒｅｈｅｎｓｉｖｅＡｐｐｌｉｃａｔｉｏｎｏｆＭＲＡＣ、ＦｕｚｙａｎｄＰＩＤＣｏｎｔｒｏｌ●陈玉东刘红波ＣｈｅｎＹｕｄｏｎｇＬｉｕＨｏｎｇｂｏ１概述ＰＩＤ控制由于算法简单、可靠性高、稳定性...     

EUCLID3

ＥＵＣＬＩＤ３ＥＵＣＬＩＤ起源于法国国家科学研究中心，由法国ＭＡＴＲＡ集团的ＭＡＴＲＡ－ＤＡＴＡＶＩ－ＳＩＯＮ公司加以商品化，并于８０年代后期合并法国雷诺汽车公司的权威的曲面设计与制造软件ＵＮＩＳＵＲＦ与ＳＵＲＦＡＰＴ，成为以实体造型为基础的、以面向...     

一类流体力学程序的向量化与并行化

一类流体力学程序的向量化与并行化袁国兴，张宝琳（北京应用物理与计算数学研究所）ＰＡＲＡＬＬＥＬＩＺＡＴＩＯＮＦＯＲＳＯＭＥＴＷＯ－ＤＩＭＥＮＳＩＯＮＡＬＦＬＵＩＤＤＹＮＡＭＩＣＡＬＰＲＯＧＲＡＭＳ￥ＹｕａｎＧｕｏｘｉｎｇ；ＺｈａｎｇＢａｏｌｉｎ（Ｉｎ...     

A Fast Hidden-line Removal Algorithm for 3-Dimensional Buildings

ＡＦＡＳＴＨＩＤＤＥＮ－ＬＩＮＥＲＥＭＯＶＡＬＡＬＧＯＲＩＴＨＭＦＯＲ３－ＤＩＭＥＮＳＩＯＮＡＬＢＵＩＬＤＩＮＧＳＱｉｎＫａｉｈｕａｉ；ＴｏｎｇＧｅｌｉａｎｇ；ＺｈａｎｇＮａｎ；ＣｈｅｎＤａｉｌｉｎ；ＬｉＹｕｎｇｕｉ；ＳｈｅｎＷｅｎｄｕＡＦＡＳＴＨＩ...     

A CONFIGURATION SYSTEM FOR FASTENER DESIGN（AN APPROACH TOWARDS COMPUTER AIDED CONCEPTUAL DESIGN）

ＡＣＯＮＦＩＧＵＲＡＴＩＯＮＳＹＳＴＥＭＦＯＲＦＡＳＴＥＮＥＲＤＥＳＩＧＮ（ＡＮＡＰＰＲＯＡＣＨＴＯＷＡＲＤＳＣＯＭＰＵＴＥＲＡＩＤＥＤＣＯＮＣＥＰＴＵＡＬＤＥＳＩＧＮ）ＧｕａｎｇＺｈｏｎｇ；ＭｉｋｅＤｏｏｎｅｒＡＣＯＮＦＩＧＵＲＡＴＩＯＮＳＹＳＴＥ...     

INTERFERENCE CHECKING IN COMPUTER-AIDED PLANT DESIGN SYSTEM

ＩＮＴＥＲＦＥＲＥＮＣＥＣＨＥＣＫＩＮＧＩＮＣＯＭＰＵＴＥＲ－ＡＩＤＥＤＰＬＡＮＴＤＥＳＩＧＮＳＹＳＴＥＭＷａｎｇＦｅｎｇＺｈａｏＨｏｎｇＮｉｕＪｕｎｙｕＡｂｓｔｒａｃｔＩｎｔｈｉｓｐａｐｅｒ，ｔｈｅｉｎｔｅｒｆｅｒｅｎｃｅｃｈｅｃｋｉｎｇｏｆｔｈｒ...     

用快速自适应组合网格方法（FAC）求解二阶椭圆型偏微分方程

用快速自适应组合网格方法（ＦＡＣ）求解二阶椭圆型偏微分方程彭志健，林振宝，石济民（香港理工学院应用数学系）ＯＮＴＨＥＣＯＭＰＵＴＡＴＩＯＮＡＬＡＳＰＥＣＴＳＯＦＴＨＥＦＡＳＴＡＤＡＰＴＩＶＥＣＯＭＰＯＳＩＴＥＧＲＩＤＭＥＴＨＯＤＦＯＲＳＯＬＶＩＮＧＳ...     

不规则网格差分法在薄板几何非线性分析中的应用

不规则网格差分法在薄板几何非线性分析中的应用李光耀（湖南大学机械系）ＡＰＰＬＩＣＡＴＩＯＮＯＦＦＩＮＩＴＥＤＩＦＦＥＲＥＮＣＥＭＥＴＨＯＤＯＮＩＲＲＥＧＵＬＡＲＧＲＩＤＳＴＯＧＥＯＭＥＴＲＩＣＡＬＬＹＮＯＮＬＩＮＥＡＲＡＮＡＬＹＳＩＳＯＦＰＬＡＴＥＳ...     

Improved cuckoo search algorithm for hybrid flow shop scheduling problems to minimize makespan

The multistage hybrid flow shop (HFS) scheduling problems are considered in this paper. Hybrid flowshop scheduling problems were proved to be NP-hard. A recently developed cuckoo search (CS) metaheuristic algorithm is presented in this paper to minimize the makespan for the HFS scheduling problems. A constructive heuristic called NEH heuristic is incorporated with the initial solutions to obtain the optimal or near optimal solutions rapidly in the improved cuckoo search (ICS) algorithm. The proposed algorithm is validated with the data from a leading furniture manufacturing company. Computational results show that the ICS algorithm outperforms many other metaheuristics.     

Improved Tabu search heuristics for the dynamic space allocation problem

The dynamic space allocation problem (DSAP) presented in this paper considers the task of assigning items (resources) to locations during a multi-period planning horizon such that the cost of rearranging the items is minimized. Three tabu search heuristics are presented for this problem. The first heuristic is a simple basic tabu search heuristic. The second heuristic adds diversification and intensification strategies to the first, and the third heuristic is a probabilistic tabu search heuristic. To test the performances of the heuristics, a set of test problems from the literature is used in the analysis. The results show that the tabu search heuristics are efficient techniques for solving the DSAP. More importantly, the proposed tabu search heuristic with diversification/intensification strategies found new best solutions using less computation time for one-half of all the test problems.     

双向启发式图搜索算法BRA^＊之研究

本文在[1]中基于模运算,提出了随机产生式系统的启发式图搜索算法RA~*.本文提出一个随机产生式系统的双向搜索的启发式图搜索算法BRA~*,证明了算法BRA~*的可采纳性,并得到了一些新的可采纳性结果.算法BRA~*的搜索效率比算法RA~*高.若启发式估价函数满足单调性限制,通过使用NP操作,则算法BRA~*的搜索空间将进一步减少.     

HYBRID ACE: COMBINING SEARCH DIRECTIONS FOR HEURISTIC PLANNING

One of the most promising trends in Domain-Independent AI Planning, nowadays, is state-space heuristic planning. The planners of this category construct general but efficient heuristic functions, which are used as a guide to traverse the state space either in a forward or in a backward direction. Although specific problems may favor one or the other direction, there is no clear evidence why any of them should be generally preferred. This paper presents Hybrid-AcE, a domain-independent planning system that combines search in both directions utilizing a complex criterion that monitors the progress of the search, to switch between them. Hybrid AcE embodies two powerful domain-independent heuristic functions extending one of the AcE planning systems. Moreover, the system is equipped with a fact-ordering technique and two methods for problem simplification that limit the search space and guide the algorithm to the most promising states. The bi-directional system has been tested on a variety of problems adopted from the AIPS planning competitions with quite promising results.     

Capacitated Clustering Problems by Hybrid Simulated Annealing and Tabu Search

The capacitated clustering problem (CCP) is the problem in which a given set of weighted objects is to be partitioned into clusters so that the total weight of objects in each cluster is less than a given value (cluster ‘capacity’). The objective is to minimize the total scatter of objects from the ‘centre’ of the cluster to which they have been allocated. A simple constructive heuristic, a R-interchange generation mechanism, a hybrid simulated annealing (SA) and tabu search (TS) algorithm which has computationally desirable features using a new non-monotonic cooling schedule, are developed. A classification of the existing SA cooling schedules is presented. The effects on the final solution quality of the initial solutions, the cooling schedule parameters and the neighbourhood search strategies are investigated. Computational results on randomly generated problems with size ranging from 50 to 100 customers indicate that the hybrid SA/TS algorithm out-performs previous simulated annealing algorithms, a simple tabu search and local descent algorithms.     

An intelligent search method for project scheduling problems

We develop an approach for implementing a real time admissible heuristic search algorithm for solving project scheduling problems with resource constraints. This algorithm is characterized by the complete heuristic learning process: state selection, heuristic learning, and search path review. The implementation approach is based on the network structure and the activity status of a project; which consists of definition of states, state transition operator, heuristic estimation, and state transition cost. The performance analysis with a benchmark problem shows that, the accumulation of heuristic learning during the search process leads to the re-scheduling of more promising activities, and finds an optimal schedule efficiently.     

A novel two-phase heuristic method for vehicle routing problem with backhauls

This paper raises a novel two-phase heuristic method to solve vehicle routing problems with backhauls. Differing from other vehicle routing problems, we consider the travel speed of vehicle to be time dependent, which will be used for the model of rush hour in an urban city. In the first phase, the original solution is generated by extending traditional heuristic methods and in the second phase, the reactive tabu search algorithm is used to optimize the original solution. We verified that this algorithm is efficient in a number of standard test cases. After comparison with the closest neighboring search algorithm, we found that the results of two-phase heuristic methods are more reasonable.     

A tabu search heuristic for the truck and trailer routing problem

Two new construction heuristics and a tabu search heuristic are presented for the truck and trailer routing problem, a variant of the vehicle routing problem. Computational results indicate that the heuristics are competitive to the existing approaches. The tabu search algorithm obtained better solutions for each of 21 benchmark problems.     

Extended guided tabu search and a new packing algorithm for the two-dimensional loading vehicle routing problem

In this paper, we develop an extended guided tabu search (EGTS) and a new heuristic packing algorithm for the two-dimensional loading vehicle routing problem (2L-CVRP). The 2L-CVRP is a combination of two well-known NP-hard problems, the capacitated vehicle routing problem, and the two-dimensional bin packing problem. It is very difficult to get a good performance solution in practice for these problems. We propose a meta-heuristic methodology EGTS which incorporates theories of tabu search and extended guided local search (EGLS). It has been proved that tabu search is a very good approach for the CVRP, and the guiding mechanism of the EGLS can help tabu search to escape effectively from local optimum. Furthermore, we have modified a collection of packing heuristics by adding a new packing heuristic to solve the loading constraints in 2L-CVRP, in order to improve the cost function significantly. The effectiveness of the proposed algorithm is tested, and proven by extensive computational experiments on benchmark instances.     

一类基于启发式搜索的激励学习算法

激励学习已被证明是在控制领域中一种可行的新方法。相比其他的方法,它能较好地处理未知环境问题,但它仍然不是一种有效的方法。幸运的是,在现实世界中,智能体总是会有一些环境的先验知识,这些能形成启发式信息。启发式搜索是一种常用的搜索方法,有很快的搜索速度,但需要精确的启发式信息,这在有些时候难以得到。文中分析比较了启发式搜索和激励学习的各自特点,提出一类新的基于启发式搜索的激励学习算法,初步的实验结果显示了较好的性能。