Thesis (Ph.D.)--University of Tulsa, 1977. / Bibliography: leaves 57-59.

Thesis (Ph.D.) -- University of Adelaide, Department of Pure Mathematics, 1976.

Thesis (Ph. D.)--Oregon State University, 2009. / Printout. Includes bibliographical references (leaves 80-86). Also available on the World Wide Web.

The objective of this thesis is to research into an integrated knowledge-based simulation method, which combines the capability of knowledge based simulation and a structured analysis method, for the design and analysis of complex and hierarchical manufacturing organizations. This means manufacturing organizations analysed according to this methodology can manage the tactical and operational planning as well as the direct operation of shop floor.

The variation of the eigenvalues and eigenfunctions of an ordinary linear self-adjoint differential operator L is considered under perturbations of the domain of L. The basic problem is defined as a suitable singular eigenvalue problem for L on the open interval ω_ < a < ω+ and is assumed to have at least one real eigenvalue λ of multiplicity k. The perturbed problem is a regular self-adjoint problem defined for L on a closed subinterval [a,b] of (ω_,ω+). It is proved under suitable conditions on the boundary operators of the perturbed problem that exactly k perturbed eigenvalues [ Formula omitted ] as a,b ⇢ ω_,ω+. Further, asymptotic estimates are obtained for [ Formula omitted ] as a,b ⇢ ω_,ω+. The other results are refinements which lead to asymptotic estimates for the eigenfunctions and variational formulae for the eigenvalues. The conditions on the limiting behaviour of the boundary operators depend strongly on the nature of the singularities ω_,ω+. If for some numberℓ⃘, ℓ⃘not an eigenvalue, linearly independent solutions of Lx = ℓ⃘x exist which are asymptotically ordered at ω_, then ω_ is palled a class 1 singularity. In the case that both ω_,ω+ are class 1 singularities, very general boundary operators permit the convergence of [ Formula omitted ], Class 2 singularities are defined as follows: If all solutions of Lx = ℓ⃘x are square-integrable on (ω_, c] for any c satisfying ω_ < c < ω+, then ω_ is called a class 2 singularity. An asymptotic ordering of the solutions is not assumed in this case. Since the behaviour of the solutions of Lx = ℓ⃘x is essentially arbitrary when both ω_,ω+ are class 2 singularities, the generality of the boundary operators has to be sacrificed to ensure that [ Formula omitted ]. Certain one end perturbation problems and examples also are considered. / Science, Faculty of / Mathematics, Department of / Graduate

There is a dearth of research on the application of hard Operational Research (OR) techniques (simulation, linear programming, goal programming, etc.) in determining optimal ordering, inventory and allocation policies for goods within distribution systems in developing countries. This study aims to assist decision making at a not-for-profit organization (NPO), Foodbank South Africa (FBSA), within its allocation system through a combined ‘soft-hard’ OR approach. Two problem-structuring tools (soft OR), Causal Mapping (CM) and Soft System Methodology’s Root Definitions (RDs), are used to structure the organization's goals (in order to gain a comprehensive understanding of the decision-context) and gain a better understanding of the ‘decision-issues’ in the allocation system at its Cape Town warehouse.

The exposure of companies to turbulence, uncertainty, and vulnerability in their supply chain results in supply chain disruption with an estimate cost of $10 million for each supply chain disruption. The purpose of this case study was to explore the strategies supply chain managers use to mitigate supply chain disruption on business performance in a pharmaceutical company in Maryland. Contingency theory of fit formed the conceptual framework for this study. Participant perceptions were elicited in interviews with 11 supply chain managers regarding strategies to mitigate risks associated with supply chain disruptions. Data from interviews and supporting documents were processed and analyzed using data source triangulation to discern emergent themes. Three main themes emerged: (a) supply chain design, planning, and forecasting; (b) flexible and multiple supplier base; and (c) resource allocation and demand management. The implications for positive social change include the potential of reducing supply chain risk, which could lead to lower prices of products for consumers, increased stakeholder satisfaction, and a higher standard of living.

Agent-based modeling (ABM) is a relatively new tool for use in electric power market research. At heart are software agents representing real-world stakeholders in the industry: utilities, power producers, system operators, and regulators. Agents interact in an environment modeled after the real-world market and underlying physical infrastructure of modern power systems. Robust simulation laboratories will allow interested parties to stress test regulatory changes with agents motivated and able to exploit any weaknesses, before making these changes in the real world. Eventually ABM may help develop better understandings of electric market economic dynamics, clarifying both delineations and practical implications of market power. The research presented here builds upon work done in collateral fields of machine learning and computational economics, as well as academic and industry literature on electric power systems. We build a simplified transmission model with agents having learning capabilities, in order to explore agent performance under several plausible scenarios. The model omits significant features of modern electric power markets, but is able to demonstrate successful convergence to stable profit-maximizing equilibria of adaptive agents competing in a quantity-based, available capacity model.

Psychological flow is a positive mental state where one is so fully concentrated in a challenging task that self-consciousness falls away, time seems to stand still, and the reward is the experience of meeting the challenge. Previous research on flow in the workplace has been performed on how to create conditions to promote its occurrence in workers, to describe its attendant individual and organizational benefits, and to measure it through self-reported means and physiologically. Such research has been focused on creative endeavors (such as the arts, sports, medicine, teaching), where individuals have high agency over the execution of activities needed to successfully complete the work. This research focuses on flow in back-office transactional work, which has been little studied to date. Transactional work are those tasks that are largely rote, repetitive, and prescribed by standardized procedures, leaving little room for agentic options. Examples of such work include data entry and bookkeeping A theory is next discussed that offers the notion of a holistic system of non-task variables working together with job tasks to create conditions conducive to increasing the likelihood of transactional workers experiencing flow. Flow will next be compared to similar constructs and their relatedness to flow will be discussed. Various flow measurement methods will be presented, along with their advantages and disadvantages. These discussions set the stage for the present set of qualitative and quantitative research efforts, whose objective is to offer support for the holistic work system approach to creating flow. First, a phenomenological study of flow in transactional workers is presented, where their lived experiences of flow are documented and the extent to which certain non-task work system variables support the occurrence of flow. Next, a proof-of-concept laboratory experiment is reviewed, where seat comfort (a non-task work system factor) is shown to be a first-order influencer of flow in the study's participants. Finally, the results of a designed experiment incorporating multiple non-task work system factors are presented and the interaction of high seat comfort and low computer screen contrast are shown to directly impact the occurrence of flow in that study's participants. Flow is also shown to predict productivity improvements in participants when combined with high seat comfort and low computer screen contrast. Additionally, certain physiological functions thought to correlate to flow are selected and measured in the participants. Lower heart rate variation partially correlates to flow. The results are applicable to the design of holistic work systems in organizations employing back-office transactional workers. Recommendations for future research are presented that will strengthen and build on the current results.

Our research considers job scheduling, a special type of resource assignment problem. For example, at a cross-docking facility trucks must be assigned to doors where they will be unloaded. The cargo on each truck has various destinations within the facility, and the unloading time for a truck is dependent on the distance from the assigned door to these destinations. The goal is to assign the trucks to doors while minimizing the amount of time to unload all trucks.;We study scheduling algorithms for problems like the cross-docking example that are different from traditional algorithms in two ways. First, we utilize real-time, where the algorithm executes at the same time as when the jobs are handled. Because the time used by the algorithm to make decisions cannot be used to complete a job, these decisions must be made quickly Second, our algorithms utilize lookahead, or partial knowledge of jobs that will arrive in the future.;The three goals of this research were to demonstrate that lookahead algorithms can be implemented effectively in a real-time context, to measure the amount of improvement gained by utilizing lookahead, and to explore the conditions in which lookahead is beneficial.;We present a model suitable for representing problems that include lookahead in a real-time context. Using this model, we develop lookahead algorithms for two important job scheduling systems and argue that these algorithms make decisions efficiently. We then study the performance of lookahead algorithms using mathematical analysis and simulation.;Our results provide a detailed picture of the behavior of lookahead algorithms in a real-time context. Our analytical study shows that lookahead algorithms produce schedules that are significantly better than those without lookahead. We also found that utilizing Lookahead-1, or knowledge of the next arriving job, produces substantial improvement while requiring the least effort to design. When more lookahead information is used, the solutions are better, but the amount of improvement is not significantly larger than a Lookahead-1 algorithm. Further, algorithms utilizing more lookahead are more complex to design, implement, and analyze. We conclude that Lookahead-1 algorithms are the best balance between improvement and design effort.