Les travaux présentés dans cette thèse portent sur la conception de systèmes de fabrication en contexte incertain. La conception d'un tel système peut être vue comme un problème d'optimisation qui consiste à trouver une configuration qui permet d'optimiser certains objectifs tout en respectant des contraintes technologiques et économiques connues. Les systèmes de fabrication étudiés dans ce mémoire sont des lignes d'assemblage et d'usinage. La première est une ligne qui se présente comme une chaîne de postes de travail où, dans chaque poste, les opérations d'assemblage s'exécutent de manière séquentielle. La deuxième, quant à elle, est une ligne particulière qui se compose de machines de transfert comportant plusieurs boîtiers multibroches où les opérations s'exécutent simultanément. Dans un premier temps, nous décrivons de différentes approches permettant de modéliser l'incertitude des données en optimisation. Une attention particulière est portée sur les deux approches suivantes : l'approche robuste et l'analyse de sensibilité. Puis, nous présentons trois applications : la conception d'une ligne d'assemblage et d'une ligne d'usinage soumises aux variations de temps opératoires et la conception d'une ligne d'assemblage avec les temps opératoires connus sous la forme d'intervalles des valeurs possibles. Pour chaque application, nous identifions les performances attendues ainsi que la complexité de la prise en compte de l'incertitude. Ensuite, nous proposons de nouveaux critères d'optimisation en adéquation avec la problématique introduite. Enfin des méthodes de résolution sont développées pour appréhender les différents problèmes mis en évidence par ces critères.

The optimum ordering strategies for the coded V-BLAST system with capacity achieving temporal codes on each stream are studied in this thesis. Mathematical representations of the optimum detection ordering strategies for the coded V-BLAST under instantaneous rate allocation (IRA), uniform power/rate allocation (URA), instantaneous power allocation(IPA) and instantaneous power/rate allocation (IPRA) are derived. For two transmit antennas, it is shown that the optimum detection strategies are based on the per-stream before-processing channel gains. Based on approximations of the per-stream capacity equation, closed-form expressions of the optimal ordering strategy under the IRA at low and high signal to noise ratio (SNR) are derived. Necessary optimality conditions under the IRA are given. Thresholds for the low, intermediate and high SNR regimes in the 2-Tx-antenna system under the IPRA are determined, and the SNR gain of the ordering is studied for each regime. Performances of simple suboptimal ordering strategies are analysed, some of which perform very close to the optimum one.

Green manure crops are critical to maintaining soil fertility in organic cropping systems. However, little research has been conducted to address their contribution to weed control. Indianhead black lentil (Lens culinaris Medikus), AC Green Fix chickling vetch (Lathyrus sativus L.), and Trapper field pea (Pisum sativum L.) are legumes developed for use as annual green manure crops in the Northern Great Plains. Currently, no plant population density recommendations exist for these three species when grown as green manure crops under weedy conditions. The objective of this research was to determine the yield-density response of these three species under weedy and weedy-free conditions and to develop plant population density recommendations for use as annual green manure crops. Each species was grown at five plant population densities (10, 24, 64, 160, and 400 plants m-2) with weedy and weed-free treatments. Wild oat (Avena fatua L.) and wild mustard (Brassica kaber (D.C.) L.C. Wheeler) were planted in weedy treatments to supplement the natural weed community. Biomass samples and soil moisture measurements were taken at early bud and full bloom to simulate when these crops would be terminated. Biomass samples from the early bud stage were analysed for total nitrogen content. Green manure biomass production for all species was lower under weedy conditions. Weed biomass in weedy treatments decreased with increasing green manure plant population density for all species. Trapper field pea was the most competitive crop while Indianhead black lentil was the least competitive. Although total plot biomass differed among species and green manure crop density, changes in soil moisture levels were not greatly affected. No significant difference in total nitrogen concentration was found among green manure species. Differences in total nitrogen accumulation occurred because of differences in biomass production. Marginal cost analysis based on green manure seed costs and their nitrogen contribution to the value of subsequent wheat crop yield were used to determine optimum plant population densities. Under weedy conditions field pea and black lentil should be planted at densities of 49-78 and 223-300 plants m-2, respectively. Under weed-free conditions plant population densities for field pea and black lentil could be reduced to 45-60 and 184-223 plants m-2, respectively. No profitable plant population density was determined for chickling vetch when assuming a lower nitrogen contribution under both weedy and weed-free conditions. However, when assuming a higher nitrogen contribution, a profitable plant population density for chickling vetch of 24 plants m-2 was determined under weedy conditions and 32 plants m-2 under weed-free conditions.

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In this paper we discuss an algorithm for the construction of D-optimal experimental designs for the parameters in a regression model when the errors have a correlation structure. We show that design points can collapse under the presence of some covariance structures and a so called nugget can be employed in a natural way. We also show that the information of equidistant design on covariance parameter is increasing with the number of design points under exponential variogram, however these designs are not D-optimal. Also in higher dimensions the exponential structure without nugget leads to collapsing of the D-optimal design when also parameters of covariance structure are of interest. However, if only trend parameters are of interest, the designs covering uniformly the whole design space are very efficient. For illustration some numerical examples are also included. (author's abstract) / Series: Research Report Series / Department of Statistics and Mathematics

Green manure crops are critical to maintaining soil fertility in organic cropping systems. However, little research has been conducted to address their contribution to weed control. Indianhead black lentil (Lens culinaris Medikus), AC Green Fix chickling vetch (Lathyrus sativus L.), and Trapper field pea (Pisum sativum L.) are legumes developed for use as annual green manure crops in the Northern Great Plains. Currently, no plant population density recommendations exist for these three species when grown as green manure crops under weedy conditions. The objective of this research was to determine the yield-density response of these three species under weedy and weedy-free conditions and to develop plant population density recommendations for use as annual green manure crops. Each species was grown at five plant population densities (10, 24, 64, 160, and 400 plants m-2) with weedy and weed-free treatments. Wild oat (Avena fatua L.) and wild mustard (Brassica kaber (D.C.) L.C. Wheeler) were planted in weedy treatments to supplement the natural weed community. Biomass samples and soil moisture measurements were taken at early bud and full bloom to simulate when these crops would be terminated. Biomass samples from the early bud stage were analysed for total nitrogen content. Green manure biomass production for all species was lower under weedy conditions. Weed biomass in weedy treatments decreased with increasing green manure plant population density for all species. Trapper field pea was the most competitive crop while Indianhead black lentil was the least competitive. Although total plot biomass differed among species and green manure crop density, changes in soil moisture levels were not greatly affected. No significant difference in total nitrogen concentration was found among green manure species. Differences in total nitrogen accumulation occurred because of differences in biomass production. Marginal cost analysis based on green manure seed costs and their nitrogen contribution to the value of subsequent wheat crop yield were used to determine optimum plant population densities. Under weedy conditions field pea and black lentil should be planted at densities of 49-78 and 223-300 plants m-2, respectively. Under weed-free conditions plant population densities for field pea and black lentil could be reduced to 45-60 and 184-223 plants m-2, respectively. No profitable plant population density was determined for chickling vetch when assuming a lower nitrogen contribution under both weedy and weed-free conditions. However, when assuming a higher nitrogen contribution, a profitable plant population density for chickling vetch of 24 plants m-2 was determined under weedy conditions and 32 plants m-2 under weed-free conditions.

Many telecommunication companies are making considerable investments to take advantage of the new business possibilities offered by 3G mobile services. Previous research on mobile network, suggests potential consumers may not adopt these 3G services provided by telecommunication companies. Given that not all new mobile telecommunication technologies are accepted by the mass market in Taiwan. Thus, there is a need for research to identify the factors that affect consumer intention to subscribe third-generation (3G) mobile services. Based on the theoretical framework of Purchase Intention Model (PIM), network effects, perceived enjoyment and optimum stimulation level, an empirical study of the mass adoption of 3G mobile services in Taiwan was conducted. Data collected from 322 users in Taiwan confirmed our hypotheses and tested against the research model. The results support the proposed model in predicting consumer intention to subscribe 3G service. This study demonstrated that perceived over performance, relative advantage, network effects, perceived enjoyment and optimum stimulation level were key factors that resulted in individuals¡¦ subscription of 3G services. Lastly, several implications for innovation technology acceptance research and 3G service management practices are discussed.

Chaotically modulated signals are used in various engineering areas such as communication systems, signal processing applications, automatic control systems. Because chaotically modulated signal sequences are broadband and noise-like signals, they are used to carry binary signals especially in secure communication systems. In this thesis, a target tracking problem under interference at chaotic communication systems is investigated. Simulating the chaotic communication system, noise-like signal sequences are generated to carry binary signals. These signal sequences are affected by Gaussian channel noise and interference while passing through the communication channel. At the receiver side, target tracking is performed using Optimum Decoding Based Smoothing Algorithm. The estimation performances of optimum decoding based smoothing algorithm at one dimensional chaotic systems and nonlinear chaotic algorithm map are presented and compared with the performance of the Extended Kalman Filter application.

Harmony search method based optimum design algorithm is presented for the grillage systems. This numerical optimization technique imitates the musical performance process that takes place when a musician searches for a better state of harmony. For instance, jazz improvisation seeks to find musically pleasing harmony similar to the optimum design process which seeks to find the optimum solution. The design algorithm considers the displacement and strength constraints which are implemented from LRFD-AISC (Load and Resistance Factor Design-American Institute of Steel Construction). It selects the appropriate W (Wide Flange)-sections for the transverse and longitudinal beams of the grillage system among 272 discrete W-section designations given in LRFD-AISC so that the design limitations described in LRFD are satisfied and the weight of the system is confined to be minimal. Number of design examples is considered to demonstrate the efficiency of the algorithm presented.

In this thesis, optimum current injection strategy for Magnetic Resonance Electrical Impedance Tomography (MREIT) is studied. Distinguishability measure based on magnetic flux density is defined for MREIT. Limit of distinguishability is analytically derived for an infinitely long cylinder with concentric and eccentric inhomogeneities. When distinguishability limits of MREIT and Electrical Impedance Tomography (EIT) are compared, it is found that MREIT is capable of detecting smaller perturbations than EIT. When conductivities of inhomogeneity and background object are equal to 0.8S and 1S respectively, MREIT provides improvement of %74 in detection capacity. Optimum current injection pattern is found based on the distinguishability definition. For 2-D cylindrical body with concentric and eccentric inhomogeneities, opposite drive provides best result. As for the 3-D case, a sphere with azimuthal symmetry is considered. Distinguishability limit expression is obtained and optimum current injection pattern is again opposite drive. Based these results, optimum current injection principles are provided and Regional Image Reconstruction (RIR) using optimum currents is proposed. It states that conductivity distribution should be reconstructed for a region rather than for the whole body. Applying current injection principles and RIR provides reasonable improvement in image quality when there is noise in the measurement data. For the square geometry, when SNR is 13dB, RIR provides decrement of nearly %50 in conductivity error rate of small inhomogeneity. Pulse sequence optimization is done for Gradient Echo (GE) and it is compared with Spin Echo (SE) in terms of their capabilities for MREIT.