计量经济分析 = Econometric analysis

Statistics for Spatial Data.

In the Hamadryas baboon, males are substantially larger than females. A troop of baboons is subdivided into a number of ‘one-male groups’, consisting of one adult male and one or more females with their young. The male prevents any of ‘his’ females from moving too far from him. Kummer (1971) performed the following experiment. Two males, A and B, previously unknown to each other, were placed in a large enclosure. Male A was free to move about the enclosure, but male B was shut in a small cage, from which he could observe A but not interfere. A female, unknown to both males, was then placed in the enclosure. Within 20 minutes male A had persuaded the female to accept his ownership. Male B was then released into the open enclosure. Instead of challenging male A , B avoided any contact, accepting A’s ownership.

Evolution and the Theory of Games

Highway Capacity Manual改訂の動向--テイラ-教授の講演より

Introduction to stochastic programming

: The rise in natural and man-made disasters in recent years has led to an increased interest in emergency evacuation planning. Athough the vast majority of the existing evacuation planning models assumes system optimal (cooperative) behavior, recent research has shown that during large evacuations people tend to exhibit selfish (noncooperative) behavior. This article presents a hybrid bilevel model that balances both behavioral assumptions (in the upper level, shelter assignment occurs in a system optimal fashion, whereas evacuees are free to choose how to reach their assigned shelters in the lower level), hence providing a model that is more in line with the current state-of-the-knowledge of human behavior during disasters. The proposed model is solved using a simulated annealing algorithm. A hypothetical evacuation scenario in Sioux Falls, South Dakota, illustrates the proposed model. We demonstrate that the resulting evacuation strategies can be significantly different from conventional system optimal evacuation plans.

A Hybrid Bilevel Model for the Optimal Shelter Assignment in Emergency Evacuations

Maritime transport chain choice by carriers, ports and shippers

Sensors are becoming increasingly critical elements in contemporary transportation systems, gathering essential (real-time) traffic information for the planning, management and control of these complex systems. In a recent paper, Hu, Peeta and Chu introduced the interesting problem of determining the smallest subset of links in a traffic network for counting sensor installation, in such a way that it becomes possible to infer the flows on all remaining links. The problem is particularly elegant because of its limited number of assumptions. Unfortunately, path enumeration was required, which – as recognized by the authors – is infeasible for large-scale networks without further simplifying assumptions (that would destroy the assumption-free nature of the problem). In this paper, we present a reformulation of this link observability problem, requiring only node enumeration. Using this node-based approach, we prove a conjecture made by Hu, Peeta and Chu by deriving an explicit relationship between the number of nodes and links in a transportation network, and the minimum number of sensors to install in order to be able to infer all link flows. In addition, we demonstrate how the proposed method can be employed for road networks that already have sensors installed on them. Numerical examples are presented throughout.

Synergistic sensor location for link flow inference without path enumeration: A node-based approach

This paper presents an evacuation route planning model that both accounts for demand uncertainty (i.e. the number of evacuees) as well as capacity uncertainty (i.e. the road capacities). To ensure reliability, the model plans for more evacuees (i.e. demand inflation) and less road capacity (i.e. supply deflation). A major contribution is that we provide a framework to determine the amount of demand inflation/supply deflation necessary to ensure a user-specified reliability level. The model is shown to be a natural generalization of previously proposed evacuation models. A small numerical case study reveals the key characteristics of the model.

Reliable evacuation planning via demand inflation and supply deflation

Periodic infrastructure maintenance is crucial for the operation of safe and efficient transportation systems. Numerous decision models for the maintenance planning problem have been proposed in the literature. However, to the best of the authors' knowledge, no model exists that simultaneously accounts for traffic dynamics and is intended for long-term planning purposes. This article addresses this gap in the literature. A mixed-integer bi-level program is introduced that minimizes the long-term maintenance cost as well as the total system travel time. For the solution approach, a genetic algorithm is utilized in conjunction with mesoscopic traffic simulation. The model is illustrated via a numerical example.

ManWo Ng

Papers

A Hybrid Bilevel Model for the Optimal Shelter Assignment in Emergency Evacuations

Maritime transport chain choice by carriers, ports and shippers

Synergistic sensor location for link flow inference without path enumeration: A node-based approach

Reliable evacuation planning via demand inflation and supply deflation

Optimal Long-Term Infrastructure Maintenance Planning Accounting for Traffic Dynamics