Self-Modeling Neural Systems

Goal-directedness is a fundamental property of all living things, but it is perhaps most easily identified in the movement patterns of animals. Ethologists have divided the basic forms of animal behavior into three categories: reproductive, defensive, and ingestive, all of which depend on the complex orchestration of motor control. In this dissertation, we use the framework of optimal control theory to model goal-directed behavior and repurpose it in new ways. We demonstrate a method for creating a hierarchical control network in which higher levels of the control hierarchy deal with tasks of increased abstractness. In a two-level system, the lower-level deals with short time-scale, low-dimensional motor control, and the higher-level is charged with longer time-scale, higher-dimensional planning. Central to our approach to joining the levels is the construction of a forward model of the behavior of the lower-level by the higher-level. Thus, we extend ideas of optimal control theory from controlling a "plant" to controlling a controller. We apply our method to the example problem of guiding a semi-truck in reverse around a field of obstacles. The lower-level controller drives the truck, and the higher-level detects obstacles and plans routes around them. In other work, we consider whether it is possible for a neural system that obeys certain biological constraints to solve optimal control problems. We exhibit a simple method to train a different kind of internal model, a neural network model of the Jacobian of the plant, and we integrate the internal model in a forward-in-time computation that produces an optimal feedback controller. We apply our method to two well-known model problems in optimal control, the torque-limited pendulum and cart-pole swing-up problems

Supply Chain

Traditionally supply chain management has meant factories, assembly lines, warehouses, transportation vehicles, and time sheets. Modern supply chain management is a highly complex, multidimensional problem set with virtually endless number of variables for optimization. An Internet enabled supply chain may have just-in-time delivery, precise inventory visibility, and up-to-the-minute distribution-tracking capabilities. Technology advances have enabled supply chains to become strategic weapons that can help avoid disasters, lower costs, and make money. From internal enterprise processes to external business transactions with suppliers, transporters, channels and end-users marks the wide range of challenges researchers have to handle. The aim of this book is at revealing and illustrating this diversity in terms of scientific and theoretical fundamentals, prevailing concepts as well as current practical applications

An Optimisation-based Framework for Complex Business Process: Healthcare Application

The Irish healthcare system is currently facing major pressures due to rising demand, caused by population growth, ageing and high expectations of service quality. This pressure on the Irish healthcare system creates a need for support from research institutions in dealing with decision areas such as resource allocation and performance measurement. While approaches such as modelling, simulation, multi-criteria decision analysis, performance management, and optimisation can – when applied skilfully – improve healthcare performance, they represent just one part of the solution. Accordingly, to achieve significant and sustainable performance, this research aims to develop a practical, yet effective, optimisation-based framework for managing complex processes in the healthcare domain. Through an extensive review of the literature on the aforementioned solution techniques, limitations of using each technique on its own are identified in order to define a practical integrated approach toward developing the proposed framework. During the framework validation phase, real-time strategies have to be optimised to solve Emergency Department performance issues in a major hospital. Results show a potential of significant reduction in patients average length of stay (i.e. 48% of average patient throughput time) whilst reducing the over-reliance on overstretched nursing resources, that resulted in an increase of staff utilisation between 7% and 10%. Given the high uncertainty in healthcare service demand, using the integrated framework allows decision makers to find optimal staff schedules that improve emergency department performance. The proposed optimum staff schedule reduces the average waiting time of patients by 57% and also contributes to reduce number of patients left without treatment to 8% instead of 17%. The developed framework has been implemented by the hospital partner with a high level of success

Maritime Empty Container Repositioning with Inventory-based Control

Ph.DDOCTOR OF PHILOSOPH

Interactions between structure and stochasticity in demogaphic models

Demography is the study of population dynamics. Populations can be considered as groups of individuals living within a given region. These simple statements encompass highly disparate systems, which respond to demographic and environmental stochasticity in predictable and unpredictable ways. The responses depend on the structure of the population, since individuals can have vastly different survival and recruitment, which, with dispersal, determine population abundance. Whilst some variation is inter-st(age) – increases in reproductive performance with age, for example – substantial intra-st(age) variation is not uncommon. Using longterm individual-based data on two disparate vertebrate populations, the focus of this thesis is the interaction between structure and stochasticity in demographic models, and consequences on resultant aspects of population growth. Structured models that incorporated variation in demographic rates detected marked differences within, between and across diverse habitats for different age-classes in both populations. These results were consistent for a wide range of scaling and definition to account for mathematical dependence. Spatial structure was more influential than age-structure in responses to stochastic predation. Despite significant changes in performance and phenotype with age, individual heterogeneity within ageclasses was vast. These results are of importance for conservation and management action, as well as predictors of evolutionary change. The population is a fundamental force in ecology and evolution. This work adds weight to the argument that characteristics of individual performance in response to variability in their environments are pivotal to increased understanding of changes in population abundance. These individual responses are dependent upon the opportunity generated by population structure. A failure to incorporate either structure or stochasticity neglects crucial aspects in population regulation, and therefore ecological and evolutionary change

Critical Review of the Literature on Marine Mammal Population Modelling

A comprehensive literature review and modeling effort have been conducted in order to determine which vital rates are most important to determining the growth and sustainability of marine mammal populations. Also addressed are the impacts of life-history, ecological, and genetic variation on vital rates and population sustainability and how much each vital parameter can change before a change in population trend would be expected. Additionally, the influence of ecological energetics and foraging strategies on vital rates and their limits of sustainable change are examined, and the nature of how an increase in sound in the marine environment might influence marine mammal behavior, and thus life functions, vital rates and population sustainability is explored. An analysis of the elasticity and sensitivity of marine mammal population models suggests that: 1) Most whale populations appear to be most sensitive to changes in adult female survival and least sensitive to calf survival. 2) Most whale populations appear to be secondarily sensitive to changes in juvenile survival and growth. 3) Most whale populations, with the exception of North Atlantic right whales (Eubalaena glacialis), appear to be insensitive to changes in fecundity at any age. 4) Adult female whales may be sensitive to changes in foraging success that limit their ability to acquire sufficient body stores of energy to sustain gestation, parturition, and lactation. 5) These results are similar to those arising from studies of non-mammalian marine predators as well as terrestrial vertebrates with similar life history characteristics. A risk assessment of the potential impacts of ocean noise on marine mammal populations based on modeling marine mammal populations suggests that: 1) Any increase in anthropogenic noise in the marine environment that reduces adult female survival, for whatever reason, is to be avoided, 2) It may be impossible to detect the impact of a change in a population vital rate on population growth because such a change may be less than the confidence interval around the estimates of the rate of growth of most marine mammal populations. 3) Sensitivity and elasticity analyses of marine mammal population models predict linear changes in marine mammal population growth rates caused by linear changes in vital rates, and do not indicate thresholds within which vital rates can change without altering population growth rates. Future research efforts should focus on the following: 1) The relationship between noise in the marine environment and adult female and juvenile survival. 2) To increase the precision and decrease the uncertainty of marine mammal population and vital rate estimates. 3) Improving the concept of potential biological removal (PBR) to reflect cumulative mortality impacts and to incorporate the effects of noise. 4) Increasing knowledge of marine mammal activity budgets seasonally and in different parts of their habitats. 5) To more fully elucidate the roles of marine mammals in their ecosystems, and their importance as sentinels of ecosystem health. 6) To exhaustively utilize existing data and models because of the cost and difficulty of gathering more data

Advances in Spatial Theory and Dynamics

This book originates from two meetings, set apart in time but closely connected by continuing collaborative efforts between researchers in an international network. The first of these meetings took place at IIASA in October 1984, organized by IIASA's Regional Issues Project under the title "Dynamic Analysis of Spatial Development". About half of the papers in this volume were presented at that meeting. These contributions have been elaborated and revised considerably during the preparation of this volume, and can now be regarded as mature papers embracing the frontiers of spatial and economic dynamics. Another set of contributions was presented during the European Summer Institute in Regional Science held at the University of Umea in June 1986. The Summer Institute was organized by CERUM in collaboration with the Departments of Economics and Geography at the same university. The contributions have been drawn from the sessions on technological change, nonlinear dynamics in spatial networks and infrastructure development. This is reflected in the three parts of the volume (1) Competition, specialization and technological change, (2) Spatial interaction, (3) Urban and regional infrastructure

AFIT School of Engineering Contributions to Air Force Research and Technology Calendar Year 1973

This report contains abstracts of Master of Science Theses, Doctoral dissertations, and selected faculty publications completed during the 1973 calendar year at the School of Engineering, Air Force Institute of Technology, at Wright-Patterson Air Force Base, Ohio

AFIT School of Engineering Contributions to Air Force Research and Technology Calendar Year 1973

This report contains abstracts of Master of Science Theses, Doctoral dissertations, and selected faculty publications completed during the 1973 calendar year at the School of Engineering, Air Force Institute of Technology, at Wright-Patterson Air Force Base, Ohio