Technical advances in the past decade have enabled the development of very fast but expensive component placement machines for the production of Printed Circuit Boards (PCBs). However, when these fast machines have to assemble small volumes of many different types of circuit boards, the machine set-up time becomes much more important than the assembly rate of each board. In order to minimize this set up time, we must try to solve the set-up/sequencing decision problem according to either the MCS (Minimizing Component Switches) or MSI (Minimizing Switching Instants) performance criterion, or both. We examine the set-up/sequencing decision problem for a single machine (work cell) which has high mix low volume production schedules. We compare and improve methods which attempt to solve this problem, and we develop our own heuristics for solving this problem when both performance criteria are of great importance. We use lower bounds to determine how good our results are, and we discuss how to adapt methods which we have looked at to different manufacturing environments.

In this thesis, we investigate the problem of minimizing printed circuit board assembly time on high-speed pick-and-place machines. As it is considered unlikely that efficient methods will be found for this problem, heuristic methods which give near optimal solutions are sought. Several such methods currently exist, but there are no comparisons made between the different methods. One of the reasons for this is the differences in the models used. In the thesis, we develop a more general model for the problem which encompasses most other models, and is robust, i.e. it can easily be adapted to different situations. We adapt two of the heuristic methods from the literature to this model, implement and test them and report the resulting assembly times. We also provide improvements to these methods, and improved lower bounding techniques for the problem. Finally, we adapt the best method to a real-world situation, namely the environment at the Mitel Corporation in Ottawa, Canada. We test this method against the sophisticated software tool currently being used at Mitel, with good results.

A good methodology for production scheduling can result in high efficiency in reducing manufacturing costs. SIMEX is an experimental simulation-based expert production scheduler developed by the author for applications in flexible flow shop systems in a dynamic factory environment. This study introduces the general framework of SIMEX. A prototype is developed on an IBM compatible PC in Prolog, MODSIM II, Visual Basic, and Visual C++ to generate feasible and acceptable schedules with a synchronous data exchange facility. In general, primary tasks of SIMEX are to meet due dates of the final products, to increase throughput by reducing the number of setups, and to reduce inventory cost in a flexible flow shop system in real time. SIMEX has also an ability to change its expert system's rule base interactively by means of a user interface. The expert system module of SIMEX allows to use heuristics, and production rules which are the simplifications that help limit the search for possible problem solutions and handling unexpected events. Simulation-based scheduler written in MODSIM II, is another module of SIMEX. It generates the schedules, repeatedly, to analyze and verify proposed design and alternatives. (Abstract shortened by UMI.)

The purpose of the thesis is to explore the design of a planning system applicable to any formal organization. To do this, issues which are related to planning systems of various types (corporate, voluntary, public) are examined in chapter I. In order to take these issues into account, the chapters II and III indicate that the concepts of system and of design should be better understood. This provides tentative guidelines for the design of systems applicable to the management of organizations (chapter IV). These first four chapters make up the first part of the thesis and provide a review of some of the basic concepts which are needed to formulate a planning system of the type envisaged. The second part of the thesis essentially describes the various components of the planning system using the guidelines and concepts provided in the first part. In chapter V, an overview of the system is provided while chapters VI, VII and VIII focus on three aspects of the planning system. Chapter VI, 'Planning Operations,' essentially revises already provided steps of the planning process and chapter VII provides guidelines for 'planning authority and responsibilities' which do not appear to have been extensively discussed in previous literature on planning systems. As a conclusion, chapter VIII presents a series of implications of a general planning system for regional planning theory and practice.

The primary focus of this research is to develop an integrated methodology for Adaptable Evacuation Planning (AEP). In case of regional evacuation caused by a hazardous event, one of main objectives of AEP is the optimal design and analysis of evacuation routes in transportation networks that will minimize total clearance time, traveled distance, and potential congestion on roads to ensure overall safety of the evacuated population. The problem under analysis is complex and challenging due to its multi-objective nature, potential congestion, blocking and queueing along routes. In addition, the hazardous event, which caused the evacuation may evolve and affect the population on egress routes, deplete the capacity of the road network and therefore make the initial assumptions of the evacuation policy invalid. To cope with the complexity of the problem, we consider it as an interaction of events in two overlapping and orthogonal networks. The first network represents a surface wild-fire propagation through a complex landscape. The second is a regional evacuation network for which route assignment optimization models are suggested. The first model utilizes a Delaunay triangulation to represent surface fire spread as movement of the fire event within the network. A data dependent procedure to construct the triangulation and estimate the rate of spread along the edges of the network is discussed. After the Delaunay triangulation is constructed, a two pass shortest path algorithm is incorporated to estimate the minimum travel time paths and fire event arrival times. In the next part of the dissertation, an integer programming (IP) formulation and model for optimal route assignment is presented, which utilizes state dependent queueing models to cope with congestion and time delays on road links. State dependent simulation software is used to evaluate performance measures of the evacuation plan: clearance time, total distance travelled and blocking probabilities. The resulting methodology allows a decision maker to adapt routing policies effectively, in case of change in hazardous event behavior, road infrastructure failure, or traffic incidents. The third model integrates the evacuation model and the fire event model and allows one to reroute the population dynamically. Finally, in the third model demonstration we illustrate proposed methodology with a case study, where regional evacuation for the Western Massachusetts is modeled.

The Multi-Mode Resource Investment Problem (MMRIP), which is a specific class of project scheduling problems, is the topic of this dissertation. A project consists of tasks that follow a specific precedence order, with each task being executed in one of its available modes. Modes for each task are different alternatives for completing a task, and may differ in their resource consumption and duration. The goal in the MMRIP is to select a mode and starting time for each task so that the project due date is met with minimal resource investment. This research is inspired by a real scheduling problem from a large engineering organization, but has applications in many other areas such as service industry and production scheduling. Even with such wide spread applicability, a review of the literature in project scheduling and related areas shows that work in the MMRIP is limited and no practical and effective methods is discovered. The opportunity exists to make both a theoretical and practical contribution in project scheduling research. In this dissertation an effective heuristic for this computationally intractable problem is developed and documented. This enhanced priority rule heuristic simultaneously considers both due date constraints and resource usage to select and schedule tasks in one decision step. This differs from previous priority rule heuristics that require two decision steps. Modifications, including stochastic search and local improvement techniques, are also developed and tested. Computational tests of the new heuristics and comparisons to existing heuristic are conducted. With 600 test instances, the best of the new heuristics performs 15% better than the best existing heuristic. The new heuristic (without stochastic search, or local improvement implemented) performs, on average, 12.6% above optimal in 30 test instances. Computation times with the new heuristic are negligible on a typical personal computer (1999 processor), for a real size problem of 35 tasks. The inclusion of stochastic search techniques takes the computation times up to several minutes.

In this thesis we aim to explore how electricity generation companies cope with the transition to a competitive environment in a newly deregulated electricity industry. Analyses and discussions are generally performed from the perspective of a Generator/Producer, otherwise they are undertaken with respect to the market as a whole. The techniques used for tackling the complex issues are diverse and wide-ranging as ascertained from the existing literature on the subject. The global ideology focuses on combining two streams of thought: the production optimisation and equilibrium techniques of the old monopolistic, cost-saving industry and; the new dynamic profit-maximising and risk-mitigating competitive industry. Financial engineering in a new and poorly understood market for electrical power must now take place in conjunction with - yet also constrained by - the physical production and distribution of the commodity.

Bibliography: leaves 131-136. / This dissertation investigates the application of Multicriteria Decision Making (MCDM) methodologies to the area of scenario based policy planning. We examine how the tools of MCDM can be used to develop a Decision Support System (DSS) that would allow management or policy planners to resolve conflicting goals and interests. Ideally, the resolution would be obtained by the various decision makers (DMs) in such a manner, that it satisfies all the relevant interest groupings at a maximum level of achievement for all concerned. This is not always possible and compromises need to be made that are fair and equitable to all the relevant interests. Stewart et al. (1993), in a report entitled: "Scenario Based Multicriteria Policy Planning for Water Management in South Africa", develop the principles of a procedure for implementing scenario based multicriteria policy planning. Their iterative procedure is illustrated in figure 2.1, chapter 2, of this paper. In this dissertation, we refine certain parts of this procedure and the two areas in particular that we have looked at are: (1) filtering a large set of policy scenarios (Background Set), that could be a continuum, to form a smaller set (Foreground Set), and (2) further reducing the smaller set to form a solution set of policy scenarios. (The generic terms "Background Set" and "Foreground Set" are defined in section 2.1 of chapter 2.) The main objectives of this study were therefore mainly twofold and are as follows: (1) to determine what MCDM methods are relevant to natural resources management (using water as a case study), and (2) to investigate how these methods need to be adopted for use in an interactive DSS. We address the first objective by surveying the literature in an attempt to identify potential MCDM approaches that are suitable to (i) reduce a large set of alternatives, analogous to the Background Set, to a more manageable smaller set, analogous to the Foreground Set of alternatives, and (ii) refine this Foreground Set in order to present the DMs with a solution set of alternatives from which University of Cape Town they will make their final selection. The literature has until now not dealt explicitly with these two issues and we had to adapt certain MCDM approaches, many of which have been developed in a linear programming context, to suit our purposes.

Bibliography: leaves 175-184. / As Bryson (1995) points out, strategic planning is particularly useful for assisting organisations and communities to deal with change. This study was carried out at a time of great change in South Africa, when a new fisheries policy was being formulated and negotiated. The research describes an intervention with a group of .fisheries managers, scientists, fishing company directors and other key stakeholders, in planning for the future management of the West Coast Rock Lobster fishery. The primary objective of the study was to consider an integrated approach to group decision support, incorporating a particular soft-OR approach, SODA, together with multi-criteria decision analysis (MCDA). An integration of these two approaches has recently been suggested by researchers, for several reasons. Firstly, different phases of an intervention usually involve different tasks. Secondly, mixing methodologies will enable different aspects of the problem to be modelled and analysed. SODA was used at the outset, for divergent exploration and structuring of the problems surrounding the development of an operational management procedure (OMP) for the fishery, including more subjective and qualitative information. Several stakeholder groups opposed the idea of an OMP in the form in which it was proposed.

This thesis provides a detailed investigation of the applicability of various economic models to the South African real sector. It has been written primarily for the statistician, and thus presentation of economic theory has been in a straightforward and, if possible, mathematical form. Chapter One provides an introduction to the application of econometric methods to economic model building. Chapters Two, Three and Four consider the theory and application of various economic models to the South African case. Chapter Five considers the relevance of money to the real sector.