Operations Research, Systems Engineering and Industrial Engineering Commons^™

Modeling Performance, Cost, Delivery, And Trip Distribution Of Demand Responsive Transit Systems With Zoning, Mahour Rahimi

Doctoral Dissertations

Demand responsive transit (DRT) services are expensive to operate, so it is crucial to understand the factors that drive the agency costs and be able to investigate and predict the effect of possible changes in specific operating parameters as well as demand and service coverage areas on total costs. In this research, we adopt the concept of the analytical model proposed by Daganzo (1978) to present continuum approximation (CA) models that can estimate important service related factors. As the first step, we propose three analytical models to approximate the operation related variables of DRT services; Fleet Size, Vehicle Hours Traveled …

Theory And Practice Of Supply Chain Synchronization, Michael Prokle

Doctoral Dissertations

In this dissertation, we develop strategies to synchronize component procurement in assemble-to-order (ATO) production and overhaul operations. We focus on the high-tech and mass customization industries which are not only considered to be very important to create or keep U.S. manufacturing jobs, but also suffer most from component inventory burden. In the second chapter, we address the deterministic joint replenishment inventory problem with batch size constraints (JRPB). We characterize system regeneration points, derive a closed-form expression of the average product inventory, and formulate the problem of finding the optimal joint reorder interval to minimize inventory and ordering costs per unit …

Decision Analytical Methods For Robust Water Infrastructure Planning Under Deep Uncertainty, Mehmet Umit Taner

Doctoral Dissertations

Deep uncertainties resulting from climate change, demographic pressures, and rapidly evolving socioeconomic conditions are challenging the way that water planners design and operate large-scale infrastructure systems. Conventionally, water infrastructures have been developed using stationary methods, assuming that the underlying uncertainties can be derived from historical data or experience. However, these methods are less useful under deeply uncertain climate and socioeconomic conditions, in which the future can be substantially different from the past and cannot be expressed by well-defined probability distributions. The recognition of deep uncertainties in long-term water resources planning has led to the development of “decision-analytical” frameworks that do …

Modeling The Economic And Environmental Performance Of Offshore Wind Energy, Alexana Cranmer

Doctoral Dissertations

Offshore wind is a growing source of energy globally. Like any energy technology, it has impacts on the environment. In the case of renewable energy, we need a way to consider the environmental benefits as well as the environmental costs. This dissertation develops a set of models to examine the economic and environmental costs and benefits and the trade-offs between them. We ask how much offshore wind energy should be sited, and where should that offshore wind energy be located? The first model estimates the economic impact of wake interactions between wind farms. Wind farm sites are chosen through a …

Multi-Criteria Decision Making When Planning Sustainable Multimodal Transportation Routes In A Linear Corridor, Marie Louis

Doctoral Dissertations

In urban and suburban locations, public transit can be seen as an effective mode of daily transportation. The majority of the time, travelers would seek the cheapest, shortest, and possibly most eco-friendly means of transit. When designing public transit network systems, transportation planners and decision-makers, with input from stakeholders, should strive to optimize transportation services to meet the needs of the population most efficiently and at the lowest cost, that is, providing a transportation system that s the three E's of the sustainability concept: environment, social equity, and economic. Previous studies have focused on sustainability as the primary concern in …

Explorations Into Machine Learning Techniques For Precipitation Nowcasting, Aditya Nagarajan

Masters Theses

Recent advances in cloud-based big-data technologies now makes data driven solutions feasible for increasing numbers of scientific computing applications. One such data driven solution approach is machine learning where patterns in large data sets are brought to the surface by finding complex mathematical relationships within the data. Nowcasting or short-term prediction of rainfall in a given region is an important problem in meteorology. In this thesis we explore the nowcasting problem through a data driven approach by formulating it as a machine learning problem.

State-of-the-art nowcasting systems today are based on numerical models which describe the physical processes leading to …

Methods For Incorporating Ecological Impacts With Climate Uncertainty To Support Robust Flood Management Decision-Making, Caitlin M. Spence

Doctoral Dissertations

Modern and historic flood risk management involves accommodating multiple sources of sources of uncertainty and potential impacts across a broad range of interrelated sectors. Sources of uncertainty that affect planning include internal climate variability, anthropogenic changes such as land use and system performance expectations, and more recently changes in climatology that affect the resources supporting the system. Flood management systems potentially impact human settlements within and beyond the systems’ scope of planning, local weather patterns, and associated ecological systems. Federal guidelines across nations have called for greater consideration of uncertainty and impacts of water resources planning projects, but methods for …