New Approach to Estimating the Standard Deviations of Lognormal Cost Variables in the Monte Carlo Analysis of Construction Risks

If soundly conducted, risk assessment could yield considerable savings for project investors. Monte Carlo Simulation (MCS) has been widely embraced by risk management guides as an instrumental tool for this purpose. This research aims to develop a new method to improve the rigor of MCS by establishing the link between parameter estimation and assessment of individual risk sources. The method is validated by virtue of its predictive power for the likelihood of a project being successful in securing investors. Eight Taiwanese sewerage Build-Operate-Transfer projects are investigated. Compared to the discounted cash flow approach, this new method can provide a more accurate prediction using the expert’s assessment as input of financial impact and occurrence likelihood of individual risks. This finding furnishes solid empirical evidence for the value MCS might add to project appraisal

Probing isospin- and momentum-dependent nuclear effective interactions in neutron-rich matter

The single-particle potentials for nucleons and hyperons in neutron-rich matter generally depends on the density and isospin asymmetry of the medium as well as the momentum and isospin of the particle. It further depends on the temperature of the matter if the latter is in thermal equilibrium. We review here the extension of a Gogny-type isospin- and momentum-dependent interaction in several aspects made in recent years and their applications in studying intermediate-energy heavy ion collisions, thermal properties of asymmetric nuclear matter and properties of neutron stars. The importance of the isospin- and momentum-dependence of the single-particle potential, especially the momentum dependence of the isovector potential, is clearly revealed throughout these studies.Comment: 27 pages, 19 figures, 1 table, accepted version to appear in EPJA special volume on Nuclear Symmetry Energ

The Information Of The Milky Way From 2MASS Whole Sky Star Count: The Bimodal Color Distributions

The J-Ks color distribution (CD) with a bin size of 0.05 magnitude for the entire Milky Way has been carried out by using the Two Micron All Sky Survey Point Source Catalog (2MASS PSC). The CDs are bimodal, which has a red peak at 0.8 < J-Ks < 0.85 and a blue peak at 0.3 < J-Ks < 0.4. The colors of the red peak are more or less the same for the whole sky, but that of the blue peak depend on Galactic latitude, (J-Ks ~ 0.35 at low Galactic latitudes and 0.35 < J-Ks < 0.4 for other sky areas). The blue peak dominates the bimodal CDs at low Galactic latitudes and becomes comparable with the red peak in other sky regions. In order to explain the bimodal distribution and the global trend shown by the all sky 2MASS CDs, we assemble an empirical HR diagram, which is composed by observational-based near infrared HR diagrams and color magnitude diagrams, and incorporate a Milky Way model. In the empirical HR diagram, the main sequence stars turnoff the thin disk is relatively bluer, (J-Ks)0 = 0.31, when we compare with the thick disk which is (J-Ks)0 = 0.39. The age of the thin/thick disk is roughly estimated to be around 4-5/8-9 Gyr according to the color-age relation of the main sequence turnoff. In general, the 2MASS CDs can be treated as a tool to census the age of stellar population of the Milky Way in a statistical manner and to our knowledge this is a first attempt to measure the age.Comment: Accepted by ApJ on Sept. 11 201

NETWORK DESIGN FOR THE TEMPORAL AND SPATIAL COLLABORATION WITH SERVICE CLASS IN DELIVERY SERVICES

The COVID-19 pandemic has significantly impacted e-commerce and the delivery service sector. As lockdowns and social distancing measures were put in place to slow the spread of the virus, many brick-and-mortar stores were forced to close, leading to an increase in online shopping. This situation led to a surge in demand for delivery services as more people turned to the internet to purchase goods. However, this increase in demand also created several challenges for delivery companies. They experienced delays in delivering packages due to increased volume, limited staff, and disruptions to supply chains. It led to more competition and increased pressure on delivery companies to improve their services and delivery times. To overcome such competition, collaboration among small and medium-sized delivery companies can be a good way to compete with larger delivery companies. By working together, small and medium-sized companies can combine their resources and expertise to offer more extensive coverage and competitive prices than they could individually. This can help them to gain market share and expand their customer base. This study proposes a network design model for collaboration with service class in delivery services considering multi-time horizon. The problem to be considered is deciding which company is dedicated to delivering certain types of items, such as regular or refrigerated items, in designated regions in each time horizon. During the agreed-upon timeframe, the companies operate, using each other's infrastructure (such as vehicles and facilities) and sharing delivery centers for the coalition's benefit to improve efficiency and reduce costs. We also propose a multi-objective, nonlinear programming model that maximizes the incremental profit of participating companies and a linearization methodology to solve it. The max-sum criterion and Shapley value allocation methods are applied to find the best solution and ensure a fair distribution of profits among the collaborating group. The efficiency of the suggested model is shown through a numerical illustration