可压缩格子Boltzmann模型的启示性稳定理论

１引言格子Ｂｏｌｔｚｍａｎｎ方法（ＬＢＭ）是近几年发展起来的一种模拟复杂系统的新方法［１］［２］［３］这种方法已经在流体力学各领域得到应用．最近,许多研究工作集中于用ＬＢＭ模型计算可压缩流体流动．Ａｌｅｘａｎｄｅｒ和Ｃｈｅｎ等［４］提出了可以计算激波的等温模型,模型中的音速是可以选择的．Ｑｉａｎ和Ｏｒｓｚａｇ［５］分析了ＬＢＧＫ模型在可压缩区域内的非线性偏差,给出了激波结构的ＬＢＭ结果．Ｑｉａｎ和Ｏｒｓｚａｇ［６］也计算了弱可压缩的高Ｒｅ数问题,并用于计算Ｋｏｌ－ｍｏｇｏｒｏｖ流．Ａｎｃｏｎａ［…     

资源有限网络计划启发式方法的评价（上）：理论分析与试验设计

在对网络计划问题分析的基础上,提出了两个衡量资源约束网络计划问题复杂性特征的度量指标-网络复杂性系数CNC及有资源约束网络的复杂性系数CRNC,并基于此设计了一种产生给定网络复杂性要求的随机活动网络发生器GRAN,最后针对资源约束的网络计划问题设计了一种评价与分析其启发式算法效果的试验模型。     

Applying GIS and Combinatorial Optimization to Fiber Deployment Plans

A decision-support system for the Fiber Deployment Plan problem is developed for the telephone cable network design in the telecommunications industry. The system employs a Geographic Information System (GIS) and uses combinatorial optimization techniques as its components. A mathematical combinatorial optimization model is formulated for the problem and a heuristic solution procedure is developed for the model. A GIS within the ESRI Arc/INFO and ArcView environment is used to provide data needed to build the mathematical combinatorial optimization model and to furnish an interface between the users and computers in data input and in solution result display. Combinatorial optimization techniques are used in the heuristic solution procedure to find good solutions for the optimization model. The developed decision-support system has been used to real life problems and has resulted in tremendous improvements in the telephone cable network design process. The user is completely satisfied with the performance of the system.     

带运输工具的网络流问题

考虑一个带运输工具的网络流问题。即由一个或者多个供应点向多个需求点通过桌种运输工具（比如货车、轮船等）供应货物的问题,目的是尽可能地降低供应成本．通过一个混和整数规划模型来描述这个问题．并利用拉格朗日松弛结合网络单纯形法得到原问题的一个下界．利用该下界结合试探法得到原问题的可行解．     

多元曲线分辨等方法和红外光谱用于二硝基五亚甲基四胺的合成反应机理研究

通过红外光谱在线监测强酸催化下硝酰胺、甲醛和氨水合成二硝基五亚甲基四胺(DPT)的反应过程, 利用渐进因子分析(EFA)、直观推导式演进特征投影法(HELP)和多元曲线分辨-交替最小二乘法(MCR-ALS)等化学计量学方法对反应过程获得的红外光谱信息进行解析, 得到了各组分纯物质的浓度变化曲线和对应的红外光谱, 并把多元曲线分辨-交替最小二乘法与直观推导式演进特征投影法的分析结果进行比较, 得出可相互验证的一致结论, 以此推测出该反应合理的反应机理. 化学计量学方法对在线红外光谱信息的分辨可以快速有效地反映DPT合成过程中各组分的浓度和红外光谱变化情况, 对其反应机理研究具有重要指导意义.     

A family of genetic algorithms for the pallet loading problem

This paper is concerned with a family of genetic algorithms for the pallet loading problem. Our algorithms differ from previous applications of genetic algorithms to two-dimensional packing problems in that our coding contains all the information needed to produce the packing it represents, rather than relying on a packing algorithm to decode each individual solution. We experiment with traditional one-dimensional string representations, and a two-dimensional matrix representation which preserves the notion of closeness between positions on the pallet. Two new crossover operators are introduced for the two-dimensional case. Our definition of solution space includes both feasible and infeasible solutions and we suggest a number of different fitness functions which penalise infeasibility in different ways and a repair operator which allows our populations to maintain feasibility. The results of experiments designed to test the effectiveness of these features are presented.     

A comparison of heuristic algorithms for cost-oriented assembly line balancing

Two new heuristic algorithms for solving cost-oriented assembly line balancing problems -the Wage-Rate-Method (WR) and the Wage-Rate-Smoothing-Method (WRS) — are presented and compared with two known heuristics — the Positional-Weight-Method (PW) and the Positional-Weight-Wage-Rate-Difference-Method (PWWD) with respect to their solution qualities. Firstly, the heuristics are outlined and their computational effort is stated. Then, a theoretical worst-case bound for the solution quality is given and the results of an extensive performance study are reported. In the study the heuristics were investigated with respect to their solution quality by solving randomly generated line balancing problems and problems from literature. It can be concluded that PWWD and WRS are generally superior to PW and WR.Parts of this research have been supported by the Stiftung Industrieforschung.     

Greedy heuristics with regret, with application to the cheapest insertion algorithm for the TSP

We consider greedy algorithms that allow partial regret. As an example we consider a variant of the cheapest insertion algorithm for the TSP. Our numerical study indicates that in most cases it significantly reduces the relative error, and the added computational time is quite small.     

Computing Approximate Solutions of the Maximum Covering Problem with GRASP

We consider the maximum covering problem, a combinatorial optimization problem that arises in many facility location problems. In this problem, a potential facility site covers a set of demand points. With each demand point, we associate a nonnegative weight. The task is to select a subset of p > 0 sites from the set of potential facility sites, such that the sum of weights of the covered demand points is maximized. We describe a greedy randomized adaptive search procedure (GRASP) for the maximum covering problem that finds good, though not necessarily optimum, placement configurations. We describe a well-known upper bound on the maximum coverage which can be computed by solving a linear program and show that on large instances, the GRASP can produce facility placements that are nearly optimal.     

团队成员选择的模型及算法

本针对组织中组建团队或重组现有团队时的成员选择问题，提出了反映团队成员之间、成员和团队之间关系的群体效用模型，并根据此模型进行团队成员的选择，从而把团队成员选择问题转化为一个组合优化问题。证明了基于群体效用模型进行团队成员选择的问题是NP-hard问题，并且提出了基于ORASP技术和禁忌算法的启发式算法，最后给出了算例。