Clustering for routing in densely populated areas

This paper introduces a new approach for generating school bus routes in a dense urban area. First, a districting algorithm is used to determine clusters including appropriate numbers of students. Then, for each cluster, a route and the stops along this route are determined. Numerical results are reported and compared with those obtained previously. Although the algorithm has been developped and tested in a specific context, it could easily be extended to more general vehicle routing problems.     

Non-classical preference models in combinatorial problems: Models and algorithms for graphs

This is a summary of the most important results presented in the authors PhD thesis (Spanjaard 2003). This thesis, written in French, was defended on 16 December 2003 and supervised by Patrice Perny. A copy is available from the author upon request. This thesis deals with the search for preferred solutions in combinatorial optimization problems (and more particularly graph problems). It aims at conciliating preference modelling and algorithmic concerns for decision aiding.Received: March 2004, MSC classification: 91B06, 90C27, 90B40, 16Y60     

Towards the Exact Minimization of BDDs—An Elitism-Based Distributed Evolutionary Algorithm

Binary Decision Diagrams (BDDs) are the state-of-the-art data structure for representation and manipulation of Boolean functions. In general, exact BDD minimization is NP-complete. For BDD-based technology, a small improvement in the number of nodes often simplifies the follow-up problem tremendously. This paper proposes an elitism-based evolutionary algorithm (EBEA) for BDD minimization. It can efficiently find the optimal orderings of variables for all LGSynth91 benchmark circuits with a known minimum size. Moreover, we develop a distributed model of EBEA, DEBEA, which obtains the best-ever variable orders for almost all benchmarks in the LGSynth91. Experimental results show that DEBEA is able to achieve super-linear performance compared to EBEA for some hard benchmarks.     

构建高效分析化学课堂的策略

针对当前分析化学课堂教学现状,从营造宽松愉悦课堂气氛、建立切实可行的预习学案和采用启发式教学方法等3个方面论述了如何构建高效分析化学课堂,以实现学生知识与能力的协调发展。     

A Combinatorial Approach to Piecewise Linear Time Series Analysis

Over recent years, several nonlinear time series models have been proposed in the literature. One model that has found a large number of successful applications is the threshold autoregressive model (TAR). The TAR model is a piecewise linear process whose central idea is to change the parameters of a linear autoregressive model according to the value of an observable variable, called the threshold variable. If this variable is a lagged value of the time series, the model is called a self-exciting threshold autoregressive (SETAR) model. In this article, we propose a heuristic to estimate a more general SETAR model, where the thresholds are multivariate. We formulate the task of finding multivariate thresholds as a combinatorial optimization problem. We develop an algorithm based on a greedy randomized adaptive search procedure (GRASP) to solve the problem. GRASP is an iterative randomized sampling technique that has been shown to quickly produce good quality solutions for a wide variety of optimization problems. The proposed model performs well on both simulated and real data.     

运筹学在复杂网络社团结构分析中的应用

社团结构研究是复杂网络这一前沿领域中的重要问题,同运筹学有着密切的关联。本文介绍了传统社团结构问题的基本定义,以及最近十年通过应用运筹学理论对该问题的研究进展。这些进展包括启发式模型,到随后的概率优化模型,以及组合优化模型。通过这些介绍,说明了运筹学方法论和基本工具在复杂系统研究中所起到的重要作用。     

Spatial competition facility location models: Definition,formulation and solution approach

Models are presented for locating a firm's production facilities and determining production levels at these facilities so as to maximize the firm's profit. These models take into account the changes in price at each of the spatially separated markets that would result from the increase in supply provided by the new facilities and also from the response of competing firms. Two different models of spatial competition are presented to represent the competitive market situation in which the firm's production facilities are being located. These models are formulated as variational inequalities; recent sensitivity analysis results for variational inequalities are used to develop derivatives of the prices at each of the spatially separated markets with respect to the production levels at each of the new facilities. These derivatives are used to develop a linear approximation of the implicit function relating prices to productions. A heuristic solution procedure making use of this approximation is proposed.     

Scheduling Tasks on Unrelated Machines: Large Neighborhood Improvement Procedures

Two approximation algorithms are presented for minimizing the makespan of independant tasks assigned on unrelated machines. The first one is based upon a partial and heuristical exploration of a search tree, which is used not only to build a solution but also to improve it thanks to a post-optimization procedure. The second implements a new large neighborhood improvement procedure to an already existing algorithm. Computational experiments show that their efficiency is equivalent to the best local search heuristics.     

Even-aged restrictions with sub-graph adjacency

Restrictions on the size and proximity of clearcuts have led to the development of a variety of exact and heuristic methods to optimize the net present value of timber harvests, subject to adjacency constraints. Most treat harvest units as pre-defined, and impose adjacency constraints on any two units sharing a common border. By using graph theory notation to define sub-graph adjacency constraints, opening size can be considered variable, which may be more appropriate for landscape-level planning. A small example data set is used in this paper to demonstrate the difference between the two types of adjacency constraints for both integer programming and heuristic solution methods.     

汽车租赁调度多目标优化模型

本文考虑一个周期的汽车租赁调度问题,在直接调运的前提下,首先以汽车租赁公司的总收益最大和总短缺损失最小为目标,建立多目标优化模型;然后提出了基于启发式的双层排序综合择优算法;最后对汽车租赁案例进行了实证研究。