A Markov chain location-allocation meta-model for hurricane relief

An emergency is a deviation from a planned course of events that endangers people, properties, or the environment. It can be described as an unexpected event that causes economic damage, destruction, and human suffering. When a disaster happens, Emergency Managers are expected to have a response plan to most likely disaster scenarios. Unlike earthquakes and terrorist attacks, a hurricane response plan can be activated ahead of time, since a hurricane is predicted at least five days before it makes landfall. This research looked into the logistics aspects of the problem, in an attempt to develop a hurricane relief distribution network model. We addressed the problem of how to efficiently and effectively deliver basic relief goods to victims of a hurricane disaster. Specifically, where to preposition State Staging Areas (SSA), which Points of Distributions (PODs) to activate, and the allocation of commodities to each POD. Previous research has addressed several of these issues, but not with the incorporation of the random behavior of the hurricane's intensity and path. This research presents a stochastic meta-model that deals with the location of SSAs and the allocation of commodities. The novelty of the model is that it treats the strength and path of the hurricane as stochastic processes, and models them as Discrete Markov Chains. The demand is also treated as stochastic parameter because it depends on the stochastic behavior of the hurricane. However, for the meta-model, the demand is an input that is determined using Hazards United States (HAZUS), a software developed by the Federal Emergency Management Agency (FEMA) that estimates losses due to hurricanes and floods. A solution heuristic has been developed based on simulated annealing. Since the meta-model is a multi-objective problem, the heuristic is a multi-objective simulated annealing (MOSA), in which the initial solution and the cooling rate were determined via a Design of Experiments. The experiment showed that the initial temperature (T0) is irrelevant, but temperature reduction (δ) must be very gradual. Assessment of the meta-model indicates that the Markov Chains performed as well or better than forecasts made by the National Hurricane Center (NHC). Tests of the MOSA showed that it provides solutions in an efficient manner. Thus, an illustrative example shows that the meta-model is practical.

Reanalysis of the 1954-1963 Atlantic Hurricane Seasons

HURDAT is the main historical archive of all tropical storms and hurricanes in the North Atlantic Basin, which includes the Caribbean Sea and Gulf of Mexico, from 1851 to the present. HURDAT is maintained and updated annually by the National Hurricane Center at Miami, Florida. Today, HURDAT is widely used by research scientists, operational hurricane forecasters, insurance companies, emergency managers and others. HURDAT contains both systematic biases and random errors. Thus, the reanalysis of HURDAT is vital. For this thesis, HURDAT is reanalyzed for the period of 1954-1963. The track and intensity of each existing tropical cyclone in HURDAT is assessed in the light of 21st century understanding and previously unrecognized tropical cyclones are detected and analyzed. The resulting changes will be recommended to the National Hurricane Center Best Track Change Committee for inclusion in HURDAT.

A comparative analysis of school satisfaction and dropout risk of middle school students attending programs for students with emotional handicaps, severe emotional disturbance and general education students attending center schools and satellite schools

This study evaluated school satisfaction as an indicator of dropout risk of students with Emotional Handicaps (EH) and students with Severe Emotional Disturbance (SED). The students attended two different kinds of middle schools in a largely urban school district in South Florida. One hundred eight students in grade 8 (ages 13-16) participated in this study. Participants were administered the National Dropout Prevention Assessment (NDPA). Forty participants with EH and SED attended a special center school. Thirty-one participants with EH and SED attended satellite programs in a regular middle school. Thirty-seven general education participants attended the same regular middle school. Overall school satisfaction scores were generated, as well as three primary factors (school, environment and personal) and 16 subscales (school atmosphere, future income, difficulty level of classwork, teacher relationships, peer relationships, intrinsic interest in classwork, school hours, classwork stress, general attitude towards school, family influence, perceived opportunity for career, future goals, travel distance, leisure time, self-appraisal of performance, and self-esteem).^ Comparison of students with EH and SED revealed that both groups of students were rated at "low risk" of becoming dropouts on the Environmental factor and the Difficulty of Schoolwork subscale. Students with EH were rated at "caution risk" risk on the Travel Distance subscale. Students with SED were rated at "high risk" on this subscale.^ There were no significant differences in school satisfaction and dropout risk between different program delivery models. There were also no significant differences for category of students (EH, SED) by school type (center school, satellite program). All students were rated at "low risk" of dropping out of school.^ There were significant differences between general education students and students with EH and SED attending satellite programs. Students with EH and SED were rated at "caution risk" for dropping out on the Travel Distance and the Leisure Time subscales. Discussion of results, implications for practice and recommendations for further research are included. ^