Dragan Cvetkovic

Preferences and their application in evolutionary multiobjective optimization

The paper describes a new preference method and its use in multiobjective optimization. These preferences are developed with a goal to reduce the cognitive overload associated with the relative importance of a certain criterion within a multiobjective design environment involving large numbers of objectives. Their successful integration with several genetic-algorithm-based design search and optimization techniques (weighted sums, weighted Pareto, weighted co-evolutionary methods, and weighted scenarios) are described and theoretical results relating to complexity and sensitivity of the algorithm are presented and discussed. Its usefulness was demonstrated in a real-world project of conceptual airframe design.

Multiobjective Satisfaction within an Interactive Evolutionary Design Environment

The paper introduces the concept of an Interactive Evolutionary Design System (IEDS) that supports the engineering designer during the conceptual/preliminary stages of the design process. Requirement during these early stages relates primarily to design search and exploration across a poorly defined space as the designers knowledge base concerning the problem area develops. Multiobjective satisfaction plays a major role, and objectives are likely to be ill-defined and their relative importance uncertain. Interactive evolutionary search and exploration provides information to the design team that contributes directly to their overall understanding of the problem domain in terms of relevant objectives, constraints, and variable ranges. This paper describes the development of certain elements within an interactive evolutionary conceptual design environment that allows off-line processing of such information leading to a redefinition of the design space. Such redefinition may refer to the inclusion or removal of objectives, changes concerning their relative importance, or the reduction of variable ranges as a better understanding of objective sensitivity is established. The emphasis, therefore, moves from a multiobjective optimization over a preset number of generations to a relatively continuous interactive evolutionary search that results in the optimal definition of both the variable and objective space relating to the design problem at hand. The paper describes those elements of the IEDS relating to such multiobjective information gathering and subsequent design space redefinition.

Agent-based support within an interactive evolutionary design system

This paper describes the use of software agents within an interactive evolutionary conceptual design system. Several different agent classes are introduced (search agents, interface agents, and information agents) and their function within the system is explained. A preference modification agent is developed and an example is given illustrating the use of agents in preference modeling.

Introducing prototype interactive evolutionary systems for ill-defined, multi-objective design environments

Abstract The paper introduces experimental prototype software that represents a number of modules within a proposed interactive evolutionary design system (IEDS). The purpose and structure of each module is briefly described and graphical user interfaces are introduced to illustrate the manner in which the prototypes may be utilised both as stand-alone modules and as linked co-operative elements. Results are presented and discussed in the light of perceived practical potential and mode of utilisation. The system under development specifically aims at the support of decision-making processes during the conceptual stages of multi-disciplinary design where the main characteristics relate to uncertainty, ill-definition and multiple objectives. Although co-evolutionary processes provide a search and exploration core, other deterministic and adaptive processes are introduced to support the requirements of the user. These include linguistic preferences, multi-agent approaches and data extraction techniques.

Designer’s Preferences and Multi—objective Preliminary Design Processes

In this paper we present a method based on preference relations for transforming non—crisp (qualitative) relationships between objectives in multi—objective optimisation into quantitative attributes (i.e. numbers).This is integrated with two multi—objective genetic algorithms (GAs): weighted sums GA and a method for combining the Pareto method with weights. Examples of the preference relations application together with traditional genetic algorithms are also presented. Some complexity issues are discussed and analysed.

Multi-objective Optimisation and Preliminary Airframe Design

In this paper we explore established methods for optimising multi-objective functions whilst addressing the problem of preliminary design. Methods from the literature are investigated and new ones introduced. All methods are evaluated within a collaborative project with British Aerospace for whole system airframe design and the basic problems and difficulties of preliminary design methodology are discussed.

Interactive Evolutionary Conceptual Design Systems

The paper introduces the concept of an interactive evolutionary conceptual design system which supports iterative designer/evolutionary search processes. Evolutionary search is seen as a means of collating high-quality engineering design information as opposed to providing a standard optimisation capability. The intention is to capture designer knowledge through designer-led, on-line design space change based upon information generated by and extracted from relatively continuous co-evolutionary search processes.