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In this thesis the problem of conceptual engineering design and the possible use of adaptive search techniques and other machine based methods therein are explored. For the multi-objective optimisation (MOO) within conceptual design problem, genetic algorithms (GA) adapted to MOO are used and various techniques explored: weighted sums, lexicographic order, Pareto method with and without ranking, VEGA-like approaches etc. Large number of runs are performed for findingZ Dth e optimal configuration and setting of the GA parameters. A novel method, weighted Pareto method is introduced and applied to a real-world optimisation problem. Decision support methods within conceptual engineering design framework are discussed and a new preference method developed. The preference method for translating vague qualitative categories (such as "more important 91 , 4m.9u ch less important' 'etc. ) into quantitative values (numbers) is based on fuzzy preferences and graph theory methods. Several applications of preferences are presented and discussed: * in weighted sum based optimisation methods; s in weighted Pareto method; * for ordering and manipulating constraints and scenarios; e for a co-evolutionary, distributive GA-based MOO method; The issue of complexity and sensitivity is addressed as well as potential generalisations of presented preference methods. Interactive dynamical constraints in the form of design scenarios are introduced. These are based on a propositional logic and a fairly rich mathematical language. They can be added, deleted and modified on-line during the design session without need for recompiling the code. The use of machine-based agents in conceptual design process is investigated. They are classified into several different categories (e. g. interface agents, search agents, information agents). Several different categories of agents performing various specialised task are developed (mostly dealing with preferences, but also some filtering ones). They are integrated with the conceptual engineering design system to form a closed loop system that includes both computer and designer. All thesed ifferent aspectso f conceptuale ngineeringd esigna re applied within Plymouth Engineering Design Centre / British Aerospace conceptual airframe design project.

ENGLISH ABSTRACT: The main aim in blending problems is to determine the best blend of available ingredients to form a certain quantity of product(s). This product should adhere to strict speci cations. In this study the best blend means the least-cost blend of ingredients (input) required to meet a minimum level of product (output) speci cations. The most prevalent tools to solve blending problems in the industry are by means of spreadsheets, simulators and mathematical programming. While there may be considerable bene t in using these types of tools to identify potential opportunities and infeasibilities, there is a potentially even greater bene t in searching automitically for alternative solutions that are more economical and e cient. Heuristics and metaheuristics are presented as useful alternative solution approaches. In this thesis di erent metaheuristic techniques are developed and applied to three typical blending problems of varied size taken from the petrochemical industry. a fourth instance of real life size is also introduced. Heuristics are developed intuitively, while metaheuristics are adopted from the literature. Random search techniques, such as blind random search and local random search, deliver fair results. Within the class of genetic algorithms the best results for all three problems were obtained using ranked tness assignment with tournament selection of individuals. Good results are also obtained by means of tabu search approaches - even considering the continuous nature of these problems. A simulated annealing approach also yielded fair results. A comparison of the results of the di erent approaches shows that the tabu search technique delivers the best result with respect to solution quality and execution time for all three the problems under consideration. Simulated annealing, however, delivers the best result with respect to solution quality and execution time for the introduced real life size problem. / AFRIKAANSE OPSOMMING: Die hoofdoelwit met die oplos van mengprobleme is om die beste mengsel van beskikbare bestandele te bepaal om 'n sekere hoeveelheid produk(te) te vervaardig. Die produk moet aan streng vereistes voldoen. Die beste kombinasie is die goedkoopste kombinasie van bestandele (toevoer) wat aan die minimum produkvereistes (afvoer) voldoen. Die algemeenste benaderings waarmee mengprobleme in die industrie opgelos word, is met behulp van sigblaaie, simulasies en wiskundige programmering. Hierdie metodes is baie nuttig om belowende oplossings of ontoelaatbaarhede te identi seer, maar dit kan potensieel meer voordelig wees om metodes te gebruik wat sistematies meer ekonomiese en e ektiewe oplossings vind. Heuristieke en metaheuristieke word as goeie alternatiewe oplossingsbenaderings aangebied. In hierdie tesis word verskillende metaheuristiekbenaderings toegepas op drie tipiese mengprobleme van verskillende groottes wat vanuit die petrochemiese industrie spruit. 'n Vierde geval met realistiese (regte wêreld) grootte word ook aangebied. Heuristieke word volgens intuïsie ontwikkel terwyl metaheuristieke aangepas word vanuit die literatuur. Lukrake soektegnieke soos die blinde lukrake soektegniek en die plaaslike lukrake soektegniek lewer redelike resultate. Binne die klas van genetiese algoritmes word die beste resultate gelewer wanneer die algoritme met 'n kombinasie van rangorde ksheidstoekenning en toernooiseleksie van individue geïmplimenteer word. Goeie resultate word ook verkry met behulp van tabusoektogbenaderings ten spyte van die kontinue aard van hierdie probleme. Gesimuleerde tempering lewer ook redelike resultate. 'n Vergelyking van die resultate van die verskillende tegnieke toon dat die tabusoektogtegniek die beste resultate met betrekking tot die kwaliteit van die oplossing sowel as uitvoertyd lewer. Gesimuleerde tempering lewer egter die beste resultate met betrekking tot die kwaliteit van die oplossing sowel as uitvoertyd vir die voorgestelde realistiese grootte probleem.

Steel space frames having irregular shapes when subjected to lateral loads caused by wind or earthquakes undergo twisting as a result of their unsymmetrical topology. As a result, torsional moment comes out which is required to be resisted by the three dimensional frame system. The members of such frame are generally made out of steel I sections which are thin walled open sections. The simple beam theory is not adequate to predict behavior of such thin-walled sections under torsional moments due to the fact that the large warping deformations occur in the cross section of the member. Therefore, it is necessary to consider the effect of warping in the design of the steel space frames having members of thin walled steel sections is significant. In this study the optimum design problem of steel space frames is formulated according to the provisions of LRFD-AISC (Load and Resistance factor design of American Institute of Steel Construction) in which the effect of warping is also taken into account. Ant colony optimization and harmony search techniques two of the recent methods in stochastic search techniques are used to obtain the solution of the design problem. Number of space frame examples is designed by the algorithms developed in order to demonstrate the effect of warping in the optimum design.

Cette thèse, réalisée en collaboration avec Sagem Défense Sécurité, porte sur l'élaboration d'une stratégie de recherche efficace pour la résolution de problèmes de planification d'itinéraires de véhicules. Nous considérons ici en particulier les problèmes de planification avec contraintes de points de passage et de "capacité" (énergie, bande passante radio) appliquées au véhicule. Ce document propose une approche originale, hybridant un algorithme de colonies de fourmis avec un solveur de Programmation par Contraintes existant. Le premier est utilisé pour résoudre rapidement une version relaxée du problème. La solution partielle obtenue est alors employée pour guider la recherche du second, par le biais d'une méthode de sonde, vers les zones les plus prometteuses de l'espace d'état. Cette approche permet ainsi de combiner la rapidité des métaheuristiques et la complétude de la programmation par contraintes. Nous montrons expérimentalement que cette approche satisfait les exigences pour une utilisation du planificateur dans un cadre embarqué. / This thesis, led in collaboration with Sagem Defence & Security, focuses on defining an efficient search strategy to solve vehicle path planning problems. This work addresses more precisely planning problems in which waypoints and "capacity" constraints (energy, radio bandwidth) are applied to vehicles.This document proposes an original approach, mixing an Ant Colony algorithm with an existing Constraint Programming solver. The former is used to fastly solve a relaxed version of the problem. The partial solution returned is then employed to guide the search of the latter, through a Probe Backtrack mechanism, towards the most promising areas of the state space. This approach allows to combine the metaheuristics solving fastness and the Constraint Programming completeness. We experimentally show that this approach meets the requirements for an on-line use of the planner.

Cellular beams became increasingly popular as an efficient structural form in steel construction since their introduction. Their sophisticated design and profiling process provides greater flexibility in beam proportioning for strength, depth, size and location of circular holes. The purpose of manufacturing these beams is to increase overall beam depth, the moment of inertia and section modulus, which results in greater strength and rigidity. Cellular beams are used as primary or secondary floor beams in order to achieve long spans and service integration. They are also used as roof beams beyond the range of portal-frame construction, and are the perfect solution for curved roof applications, combining weight savings with a low-cost manufacturing process. The purpose of the current research is to study optimum design, ultimate load capacity under applied load and finite element analysis of non-composite cellular beams. The first part of the research program focuses on the optimum design of steel cellular beams using one of the stochastic search methods called &ldquo / harmony search algorithm&rdquo / . The minimum weight is taken as the design objective while the design constraints are implemented from the Steel Construction Institute. Design constraints include the displacement limitations, overall beam flexural capacity, beam shear capacity, overall beam buckling strength, web post flexure and buckling, vierendeel bending of upper and lower tees and local buckling of compression flange. The design methods adopted in this publication are consistent with BS5950. In the second part of the research, which is the experimental work, twelve non-composite cellular beams are tested to determine the ultimate load carrying capacities of these beams under using a hydraulic plug to apply point load. The tested cellular beam specimens have been designed by using harmony search algorithm. Finally, finite element analysis program is used to perform elastic buckling analysis and predict critical loads of all steel cellular beams. Finite element analysis results are then compared with experimental test results for each tested cellular beam.