Optimization techniques with knowledge based control in ship concept design

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.An integrated computational approach to Ship Concept Design using optimization techniques and a knowledge base to control the optimization process has been developed. The system automates both synthesis and analysis; analysis by the repeated sequential use of Design Theory Modules and synthesis through the optimization process, which compromises conflicting requirements, subject to constraints. The intention of this work has been to find a better approach to automated design synthesis and at the same time employ detailed analytical tools such as a three-dimensional hull-form definition and engineering analysis modules. Optimization techniques and a knowledge base are combined to achieve the desired capabilities, taking advantage of the benefits optimization can bring using goal oriented methods and exploratory searches, alongside a knowledge base that controls the synthesis process rather than the design. A function mapping strategy has been developed to provide a multiple-parametric view of regions of the optimization objective function and constraints. A discussion is included on the role of further applications of expert systems to design systems in both synthesis and analysis and their possible interference with creativity and innovation. Two design examples are provided, one showing the application of the system using optimization and the other adding the use of the knowledge base. The results are compared and discussed.National Council of Research (CNPq - Brazil

Early aspects: aspect-oriented requirements engineering and architecture design

This paper reports on the third Early Aspects: Aspect-Oriented Requirements Engineering and Architecture Design Workshop, which has been held in Lancaster, UK, on March 21, 2004. The workshop included a presentation session and working sessions in which the particular topics on early aspects were discussed. The primary goal of the workshop was to focus on challenges to defining methodical software development processes for aspects from early on in the software life cycle and explore the potential of proposed methods and techniques to scale up to industrial applications

On the Identification of Agents in the Design of Production Control Systems

This paper describes a methodology that is being developed for designing and building agent-based systems for the domain of production control. In particular, this paper deals with the steps that are involved in identifying the agents and in specifying their responsibilities. The methodology aims to be usable by engineers who have a background in production control but who have no prior experience in agent technology. For this reason, the methodology needs to be very prescriptive with respect to the agent-related aspects of design

Root Cause Analysis in Business Processes

Conceptual modeling is an important tool for understanding and revealing weaknesses of business processes. Yet, the current practice in reengineering projects often considers simply the as-is control flow and uses the respective model barely as a reference for brain-storming about improvement opportunities. This approach heavily relies on the intuition of the participants and misses a clear description of steps to identify root causes of problems. In contrast to that, this paper introduces a systematic methodology to detect and document the quality dimension of a business process. It builds on the definition of softgoals for each process activity, of correlations between softgoals, and metrics to measure the occurrence of quality issues. In this regard our contribution is a foundation of root-cause analysis in business process modeling, and a conceptual integration of goal-based and activity-based approaches to capturing processes

Model Based Development of Quality-Aware Software Services

Modelling languages and development frameworks give support for functional and structural description of software architectures. But quality-aware applications require languages which allow expressing QoS as a first-class concept during architecture design and service composition, and to extend existing tools and infrastructures adding support for modelling, evaluating, managing and monitoring QoS aspects. In addition to its functional behaviour and internal structure, the developer of each service must consider the fulfilment of its quality requirements. If the service is flexible, the output quality depends both on input quality and available resources (e.g., amounts of CPU execution time and memory). From the software engineering point of view, modelling of quality-aware requirements and architectures require modelling support for the description of quality concepts, support for the analysis of quality properties (e.g. model checking and consistencies of quality constraints, assembly of quality), tool support for the transition from quality requirements to quality-aware architectures, and from quality-aware architecture to service run-time infrastructures. Quality management in run-time service infrastructures must give support for handling quality concepts dynamically. QoS-aware modeling frameworks and QoS-aware runtime management infrastructures require a common evolution to get their integration