All automobile manufacturing companies, Google and Microsoft have announced recently their production of the Fully Automated Autonomous Vehicles (FAAVs), otherwise known as driverless cars. A few FAAVs would be availa...All automobile manufacturing companies, Google and Microsoft have announced recently their production of the Fully Automated Autonomous Vehicles (FAAVs), otherwise known as driverless cars. A few FAAVs would be available in the market as early as in 2018, but mostly in 2020’s. When FAAVs will be available to and become affordable by the average consumers, the implications to the society would be far reaching. The purpose of the paper is to examine the prospect of the popularity of FAAVs and their socio-economic implications to the future society of the World. The paper examines potential impacts on selected sectors of the society including changes in demand for automobiles, its impact on the use of oil, on the environment, and on urban land uses, to list a few.展开更多
Extreme flood events are becoming more frequent and intense in recent times, owing to climate change and other anthropogenic factors. Nigeria, the case-study for this research experiences recurrent flooding, with the ...Extreme flood events are becoming more frequent and intense in recent times, owing to climate change and other anthropogenic factors. Nigeria, the case-study for this research experiences recurrent flooding, with the most disastrous being the 2012 flood event that resulted in unprecedented damage to infrastructure, displacement of people, socio-economic disruption, and loss of lives. To mitigate and minimize the impact of such floods now and in the future, effective planning is required, underpinned by analytics based on reliable data and information. Such data are seldom available in many developing regions, owing to financial, technical, and organizational drawbacks that result in short-length and inadequate historical data that are prone to uncertainties if directly applied for flood frequency estimation. This study applies regional Flood Frequency Analysis (FFA) to curtail deficiencies in historical data, by agglomerating data from various sites with similar hydro-geomorphological characteristics and is governed by a similar probability distribution, differing only by an “index-flood”;as well as accounting for climate variability effect. Data from 17 gauging stations within the Ogun-Osun River Basin in Western Nigeria were analysed, resulting in the delineation of 3 sub-regions, of which 2 were homogeneous and 1 heterogeneous. The Generalized Logistic distribution was fitted to the annual maximum flood series for the 2 homogeneous regions to estimate flood magnitudes and the probability of occurrence while accounting for climate variability. The influence of climate variability on flood estimates in the region was linked to the Madden-Julian Oscillation (MJO) climate indices and resulted in increased flood magnitude for regional and direct flood frequency estimates varying from 0% - 35% and demonstrate that multi-decadal changes in atmospheric conditions influence both small and large floods. The results reveal the value of considering climate variability for flood frequency analysis, especially when non-stationarity is established by homogeneity analysis.展开更多
This study introduces the same-day delivery time-guarantee(SDDTG)problem for supporting online retail.In the SDDTG,orders are placed online and are processed and delivered from a depot to customer locations in the sam...This study introduces the same-day delivery time-guarantee(SDDTG)problem for supporting online retail.In the SDDTG,orders are placed online and are processed and delivered from a depot to customer locations in the same day.The problem seeks optimal delivery time guarantees to offer customers as they consider making purchases to increase purchase decision likelihood while accounting for delivery-related,supply-side costs that can affect profits.Time guarantees are decision variables rather than parameters(as is typical)and are designed around anticipated customer satisfaction levels and purchase likelihoods.Delivery deadlines are not merely given to customers once they make their purchases,but rather the attractiveness of the offered delivery guarantees affects whether they make their purchases,i.e.,whether demand is realized.The problem is conceptualized as a multistage,stochastic,mixed-integer program in which uncertainties associated with customer reaction to delivery time guarantee offers and their arrival over time are captured.Given a shrinking horizon over a fixed planning horizon,the multi-stage program is approximated by a series of two-stage programs.A parallelized progressive hedging solution methodology is proposed and insights from its application on a case study.The problem recognizes tradeoffs between meeting promised delivery times and capturing the market.展开更多
文摘All automobile manufacturing companies, Google and Microsoft have announced recently their production of the Fully Automated Autonomous Vehicles (FAAVs), otherwise known as driverless cars. A few FAAVs would be available in the market as early as in 2018, but mostly in 2020’s. When FAAVs will be available to and become affordable by the average consumers, the implications to the society would be far reaching. The purpose of the paper is to examine the prospect of the popularity of FAAVs and their socio-economic implications to the future society of the World. The paper examines potential impacts on selected sectors of the society including changes in demand for automobiles, its impact on the use of oil, on the environment, and on urban land uses, to list a few.
文摘Extreme flood events are becoming more frequent and intense in recent times, owing to climate change and other anthropogenic factors. Nigeria, the case-study for this research experiences recurrent flooding, with the most disastrous being the 2012 flood event that resulted in unprecedented damage to infrastructure, displacement of people, socio-economic disruption, and loss of lives. To mitigate and minimize the impact of such floods now and in the future, effective planning is required, underpinned by analytics based on reliable data and information. Such data are seldom available in many developing regions, owing to financial, technical, and organizational drawbacks that result in short-length and inadequate historical data that are prone to uncertainties if directly applied for flood frequency estimation. This study applies regional Flood Frequency Analysis (FFA) to curtail deficiencies in historical data, by agglomerating data from various sites with similar hydro-geomorphological characteristics and is governed by a similar probability distribution, differing only by an “index-flood”;as well as accounting for climate variability effect. Data from 17 gauging stations within the Ogun-Osun River Basin in Western Nigeria were analysed, resulting in the delineation of 3 sub-regions, of which 2 were homogeneous and 1 heterogeneous. The Generalized Logistic distribution was fitted to the annual maximum flood series for the 2 homogeneous regions to estimate flood magnitudes and the probability of occurrence while accounting for climate variability. The influence of climate variability on flood estimates in the region was linked to the Madden-Julian Oscillation (MJO) climate indices and resulted in increased flood magnitude for regional and direct flood frequency estimates varying from 0% - 35% and demonstrate that multi-decadal changes in atmospheric conditions influence both small and large floods. The results reveal the value of considering climate variability for flood frequency analysis, especially when non-stationarity is established by homogeneity analysis.
基金supported by the U.S.National Science Foundation(Grant No.1823474).
文摘This study introduces the same-day delivery time-guarantee(SDDTG)problem for supporting online retail.In the SDDTG,orders are placed online and are processed and delivered from a depot to customer locations in the same day.The problem seeks optimal delivery time guarantees to offer customers as they consider making purchases to increase purchase decision likelihood while accounting for delivery-related,supply-side costs that can affect profits.Time guarantees are decision variables rather than parameters(as is typical)and are designed around anticipated customer satisfaction levels and purchase likelihoods.Delivery deadlines are not merely given to customers once they make their purchases,but rather the attractiveness of the offered delivery guarantees affects whether they make their purchases,i.e.,whether demand is realized.The problem is conceptualized as a multistage,stochastic,mixed-integer program in which uncertainties associated with customer reaction to delivery time guarantee offers and their arrival over time are captured.Given a shrinking horizon over a fixed planning horizon,the multi-stage program is approximated by a series of two-stage programs.A parallelized progressive hedging solution methodology is proposed and insights from its application on a case study.The problem recognizes tradeoffs between meeting promised delivery times and capturing the market.
