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The problem to which this thesis is addressed is known as the n by m scheduling problem. It can be briefly described as follows: n commodities are, each in a prescribed order, to be processed on one or more of m facilities which are initially idle, ready to provide service, and uncommited in the future. All ofthe n commodities are ready to be processed initially, and each must be processed for a prescribed period of time on each facility to which it is to be routed.

Implemented to provide the users with as much power as possible, LETEXT conforms to design criteria which include service to the users and security and privacy of the users' information.

First-order methods for convex and nonconvex optimization have been an important research topic in the past few years. This talk studies and develops efficient algorithms of first-order type, to solve a variety of problems. We first focus on the widely studied gradient-based methods in composite convex optimization problems that arise extensively in compressed sensing and machine learning.

This study considers the effect of priority dispatching in a labor and machine limited production system. A simulation model of an actual shop is developed using GASP II. The shop is characterized as a flow shop with cycling in which lots are subject to stochastic yields and reworks. Five labor sections, each operating on three shifts, exist in the shop.

My project narrows in on a specific segment of academic life—the first year—in order to consider how a new student's experiences navigating an unfamiliar institution, through and among literary texts, helps us to understand contemporary imaginings of the university and the role of literature within those models of collegiate education.

Methods used by electric power companies for estimating future loads as a basis for timing generating capacity additions have been examined. It has been found that these estimates deviate widely from time to time from the loads subsequently experienced. A method is developed for interrelating the total annual energy requirements, annual energy sales by classes, and the annual peak loads as a possible basis for improving the timing of generating capacity additions.

The conversion of a decision table into an optimal decision tree is an integral part of most decision table compilers. This thesis establishes some fundamental concepts of a heuristic approach to the conversion of limited entry decision tables into decision trees and proposes algorithms for the latter two objectives.

A cryogenic refrigerator using an expander with a reciprocating displacer or piston which has a thermal gradient from one end to the other suffers a loss of refrigeration due to heat transfer between the displacer/piston and the cylinder (shuttle heat transfer). This loss can be eliminated by designing an annular thermal regenerator on the outside diameter of the displacer/piston in such a manner as to match the temperature profile of the displacer/piston and the cylinder wall throughout the cycle.

Utilizing a sample of 214 clinical, counseling, and school psychology doctoral students recruited from APA-accredited programs, the present mixed-methods study examined whether and to what extent demographic variables and interprofessional experiences—both educational and practice oriented—were related to their self-reported attitudes toward interprofessional health care teams (IPTs) as well as their readiness for interprofessional learning.

This work focuses on developing optimization models and algorithms to solve problems in electricity networks and renewable energy. The steady rise of electricity demand in the world, along with the deployment of volatile renewable energy resources in greater quantities, will require many researchers, policymakers, and other stakeholders in the field of power management to understand these challenges and use new methods, approaches and technologies to modernize the electric grid.