Hozumi Morohosi

A Practical Approach to the Error Estimation of Quasi-Monte Carlo Integrations

There have been few studies on practical error estimation methods of quasi-Monte Carlo integrations. Recently, some theoretical works were developed by Owen to analyze the quasi-Monte Carlo integration error. However his method given by those works is complicated to be implemented and needs huge computational efforts, so it would be of some interest to investigate into a simple error estimation method. In this paper, we will use a simple method, and give some theoretical considerations on the errors given by these two methods. Numerical experiments are also reported.

Measuring the network robustness by Monte Carlo estimation of shortest path length distribution

Two kinds of robustness measure for networks are introduced and applied to the road network systems in Japan. One is on the connectivity of randomly chosen pair of vertices, another is on the shortest path length between pair of connected vertices. We devise Monte Carlo methods for the computation of two measures.

Hypercube simulation analysis for a large-scale ambulance service system

A simple yet powerful simulation model for an ambulance service system is devised and applied to a large-scale ambulance system in the Tokyo metropolis. Our simulation can provide useful measures for the location analysis of ambulance stations, which are rarely incorporated in traditional optimal location models, although they are seemingly very important for designing a reliable and efficient emergency system. Comparing simulation output and actual data enables us to investigate the present ambulance system as well as check the validity and limitations of our model. Then we use the model to evaluate solutions to the ambulance station location problem.

Applying path‐counting methods for measuring the robustness of the network‐structured system

We consider the path-counting problem that asks how many paths exist between any two different nodes in a network after deleting an arbitrary number of edges or nodes from the original network. Using path-counting methods, we propose a quantitative method for measuring the robustness of the network-structured system. First we define the connectivity function and attempt to obtain the expected connectivity function for the network. Applying the Monte Carlo method, we estimate expected edge deletion and node deletion connectivity functions when an arbitrary number of edges or nodes are deleted from the original network. We attempt to approximate the expected edge deletion connectivity function using an appropriate nonlinear function with two parameters. We also show the numerical results of applying the path-counting method with their analysis in order to quantitatively evaluate the connectivity for some special types of networks.

Stable Connectivity of Networks and Its Monte Carlo Estimation

We propose a criterion for the stability of network-structured systems, which counts the number of paths between all the pairs of distinct nodes in the random network. In order to estimate the criterion we introduce a Monte Carlo algorithm. Some numerical experiments are presented to show the performance of our criterion.

Developing a Green Path Power Expansion Plan in Indonesia by Applying a Multiobjective Optimization Modeling Technique

AbstractThis paper aims to apply a multiobjective optimization modeling technique to a power expansion problem evaluating two objectives functions: minimizing the power generating cost and minimizing CO2 emissions, between which there is a tradeoff. A convex curve is obtained representing the relationship between the generating cost (Rp/kWh) and CO2 emissions (ton). This represents a bad-luck curve where there is an increasing marginal cost to reduce 1 t of CO2 emissions. This is because most of the less-carbon-intensive power plants consume oil, which has the highest fuel cost. Instead of simply minimizing CO2 emissions, this paper argues that Indonesia needs to pursue technology to switch from steam coal subcritical technology to supercritical and ultra-supercritical technology to reduce CO2 emissions. It is further found that the generating cost will increase by less than 1.6% and yearly CO2 emissions can be reduced by about 6.9% by adopting supercritical technology. This implies that adopting ultra-su...

Two Approaches to Cooperative Covering Location Problem and Their Application to Ambulance Deployment

This study proposes two approximation methods to define the coverage probability in ambulance location problems based on the model of cooperative covering proposed by Berman et al. (IEE Trans. 40, 232–245, 2010, [1]) as an extension to classical covering problems. A key ingredient of the model is the estimation of the coverage probability by multiple facilities. We introduce a simple parametric model for the travel time of ambulances and propose two methods to calculate the coverage probability approximately. We report and discuss two solutions obtained from computations using actual data.