Thesis (M.S. in Operations Research)--Naval Postgraduate School, June 2004. / Thesis advisor(s): Richard E. Rosenthal, Thomas Hoivik. Includes bibliographical references (p. 77). Also available online.

Thesis (Ph. D.)--University of Texas at Austin, 2003. / Supervisor: J. Wesley Barnes. Vita. Includes bibliographical references. Available also from UMI Company.

Thesis (M.S. in Operations Research)--Naval Postgraduate School, September 1990. / Thesis Advisor(s): Parry, Samuel H. Second Reader: Hoffman, James. "September 1990." Description based on title screen as viewed on December 18, 2009. DTIC Descriptor(s): Routing, Tactical Analysis, Experimental Data, Models, Theses, Variables, Operation, Active Duty, Casualties, Officer Personnel, Army Operations, Decision Aids, Marine Corps Operations, Measurement, Methodology. DTIC Identifier(s): Optimization. Author(s) subject terms: CAMMS/SHAW, Tactical Optimum Path. Includes bibliographical references (p. 108-110). Also available in print.

Thesis (M.S. in Operations Research)--Naval Postgraduate School, September 1990. / Thesis Advisor(s): Parry, Samuel H. Second Reader: Caldwell, William J. "September 1990." Description based on title screen as viewed on December 18, 2009. DTIC Descriptor(s): Air Defense, Artillery, Simulation, Warfare, Theater Level Operations, Aircraft, Strategy, Defense Systems, Point Defense, Loads(Forces), Attack, Theses, Missions, Army, ADA Programming Language, Bombing, USSR, Computerized Simulation, Models. DTIC Identifier(s): Belt Defense. Author(s) subject terms: JTLS, ADA strategy, point defense, belt defense. Includes bibliographical references (p. 56). Also available in print.

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A mean-variance stochastic optimization algorithm is developed for long-term operation of multi-reservoir systems. Two important factors in reservoir management problems are the prediction on benefits (expected value of water in storage at the end of a simulation period) and inflows. These, together with information on the state of the reservoir, constitute the information input to the decision-making unit and fully determine the release decision. Traditional optimization models are based on deriving a release policy that optimizes a given objective. Such approaches do not account for the fact that the release, which is a function of random inflow and thus a random variable itself, may have a distribution with different variance measure based on the available forecasts. While much effort has been placed in developing an efficient method to incorporate the uncertainty in inflows and their spatial and temporal correlations in reservoir operations, very few approaches (e.g., Dynamic Programming) use the benefit (Cost-to-Go) in a real-time implementation. The proposed temporal decomposition approach takes into account the value of water at the end of the operating horizon as a boundary condition. The first-period decision is common between forecasts while the decisions for remaining periods vary with forecast sequence. The parameter iteration method (Gal, 1979; Zhang et al., 1991) is used to approximate the value of the benefit function (or the Cost-to-Go). In desire to minimize the variance of the objective (expected return) to obtain robust operating (release) policy, a mathematically sound mean-variance formulation is implemented in real time that considers spatial and temporal correlation in streamflows. The foundation of the formulation presented is rooted in stochastic portfolio optimization scheme of Markowitz (1959). The mathematical routines for forecasts and optimization are utilized to set up a user-friendly Decision Support System for multi-reservoir management under hydroclimatic uncertainties.

Adaptive traffic control systems need to continuously monitor traffic conditions and predict immediate traffic conditions to respond to changes in both recurrent and nonrecurrent traffic patterns. One measure of traffic conditions is the number of turning vehicles at intersections and freeway offramps. Split parameters may be estimated from the numbers of turning vehicles, and along with upstream traffic counts, these may be used to predict the numbers of downstream vehicle arrivals. This study develops several responsive methods to estimate split parameters for four-legged intersections and freeway segments from vehicle counts. For intersections, these methods depend on the geometric layout of the intersection and the signal stage. The vehicle counts are collected by signal stages and lanes. The split parameters or turning proportions are estimated for each signal stage and, then they are combined to estimate the turning proportions for the entire interval. Some methods need counts for only one cycle to estimate turning proportions while others need additional data. For those methods that need additional data, four closed-form estimation methods are developed. Two methods need prior turning proportion estimates: (1) maximum entropy (ME) and (2) generalized least-squared error (GLS). The other methods require counts for three cycles: (3) least-squared error (LS) and (4) least-squared error/generalized least-squared error (LS/GLS). Results from these methods are compared with each other. The ME, GLS and LS methods which use cycle counts are also developed and their results are compared with the results of their stage-count counterparts. For freeway segments, a virtual box method for consistent vehicle counting is developed. Three split parameter estimation methods are developed for freeway segments. One method, GLS, uses counts, from one virtual box and requires prior split parameter estimates. The other methods, LS and GLS/LS, need several virtual boxes, depending on the number of interchanges in the freeway segment. Split parameter estimation approaches are also developed for small road networks by combining split parameters from individual intersections and freeway segments.

This document presents a novel representation and evaluation framework for organizational structures. The SES Enterprise Alternative Evaluator (SEAE), while adhering to the broader focus of developing a design environment for manufacturing system configurations, will be used to design and evaluate a single product process. Enterprise representation, normally approached through the categorical qualitative and quantitative descriptive attributes of evaluation objectives, did not have a framework specifically focused on hierarchical enterprise design prior to this dissertation. The SES, in representing the manufacturing enterprise, includes alternative manufacturing system components within the design structure through entity specialization. SEAE enumeration produces the best set of these alternatives relative to the objectives during enterprise evaluation. The motivation for this research was two-fold. A primary consideration was to provide enterprise designers with a modular, flexible tool, incorporating current state-of-the-art modeling and simulation capabilities for use in hypothesis testing, development, and analysis. Enterprise modeling is presently devoid of a framework for simultaneously combining the strategic, tactical, and financial enterprise design considerations along the lines of common organization function hierarchical decompositions. The present approach is to provide a design structure, usually to combine prescriptive and descriptive methods, to achieve the representation. Preliminary results of this tool's use are presented for designing and evaluating Terrasun L. L. C.'s manufacturing system.

Cellular manufacturing has been extensively adopted as a measure to reduce cycle time, increase productivity, and improve product quality. The past research in cellular manufacturing has focused on the methodology for identification of machine groups, part families, and determination of processing routes while the relocation of existent workers into cells and their training for cellular manufacturing environment have been ignored. However, several industrial surveys show that human and administrative issues are a major unsolved problem in implementing cells. Human issues in the cell formation process have received little attention in the literature. This dissertation develops methods for guiding the assignment of workers to cells and determination of training plans and task assignments for workers. An integer programming model is first proposed to determine the assignment of workers to cells and the aggregate training needs for each cell with consideration of meeting the technical and administrative skill requirements in each cell. In addition to the technical and administrative skills, team synergy level predicted on the basis of the combination of individual personality-related traits, and individual job fitness are then included in the consideration for building high performance teams. A mixed integer programming model is formulated with objective to create effective manufacturing teams meeting cell requirements with low training cost, high team synergy level, and compatibility between workers and tasks. Several solution methods including greedy heuristics, beam search, filtered beam search, and simulated annealing techniques are developed for solving the mathematical models. They are tested and compared to a standard optimization software for a set of test problems. Results indicate that problem size, initial mix of skills, and the skill requirements of cells in the data set impact the difficulty of obtaining good solutions. Nevertheless, it appears that heuristics such as beam search are capable of obtaining good solutions with reasonable computational effort. Directions for future work are discussed at the conclusion of this dissertation.

The agent system specification, the agent system implementation and the agent system verification are three essential issues to build an agent system. Many works have been done for the first two issues in recent years. However, as a result of a lack in formal agent modeling techniques, little effort has been made to address the verification issue, which impedes the agent technique a smooth transition from the research lab to the desk of everyday computer engineers. Motivated by this fact and its significance, it is our objective in this dissertation to establish a systematic method for modeling and analysis of agent systems. An approach to combine the agent belief-desire-intention (BDI) theory and the Petri net transducer (PNT) theory is proposed. The resulting belief-planner-actuator model specifies individual behaviors of agents successfully and bridges the gap among belief, desire and intention of agents seamlessly. A set of agent communication protocols is developed to specify the agent social behavior. Theorems on analyzing the Petri Net underlying those protocols are proposed and proved. Based upon the proposed communication protocols, three agent social behavior models are proposed here: direct coordination, meeting-oriented coordination and blackboard-based coordination. To further exploits the power of the agent communication protocols, a framework to model the mobility of agents is proposed. The framework includes a set of stationary agents (SA) and mobile agents (MA). The agent learning ability is modeled based upon the probabilistic Petri net transducer theory. The individual agent learning behavior is then extended to multiple-agent systems, where the game theory and the agent learning model are combined to achieve a number of agent interaction strategies. These strategies include: self-interested learning, complete cooperative learning, bargaining learning and coordinated learning. Several simulation studies have been conducted to investigate the effectiveness of the proposed agent model. This model is further evaluated through its application to the WAVES (web based audio video educational systems) project and the results have indicated that the proposed method is ideal in analysis of agent systems.