Minimisation des perturbations et parallélisation pour la planification et l'ordonnancement

Nous étudions dans cette thèse deux approches réduisant le temps de traitement nécessaire pour résoudre des problèmes de planification et d'ordonnancement dans un contexte de programmation par contraintes. Nous avons expérimenté avec plusieurs milliers de processeurs afin de résoudre le problème de planification et d'ordonnancement des opérations de rabotage du bois d'oeuvre. Ces problèmes sont d'une grande importance pour les entreprises, car ils permettent de mieux gérer leur production et d'économiser des coûts reliés à leurs opérations. La première approche consiste à effectuer une parallélisation de l'algorithme de résolution du problème. Nous proposons une nouvelle technique de parallélisation (nommée PDS) des stratégies de recherche atteignant quatre buts : le respect de l'ordre de visite des noeuds de l'arbre de recherche tel que défini par l'algorithme séquentiel, l'équilibre de la charge de travail entre les processeurs, la robustesse aux défaillances matérielles et l'absence de communications entre les processeurs durant le traitement. Nous appliquons cette technique pour paralléliser la stratégie de recherche Limited Discrepancy-based Search (LDS) pour ainsi obtenir Parallel Limited Discrepancy-Based Search (PLDS). Par la suite, nous démontrons qu'il est possible de généraliser cette technique en l'appliquant à deux autres stratégies de recherche : Depth-Bounded discrepancy Search (DDS) et Depth-First Search (DFS). Nous obtenons, respectivement, les stratégies Parallel Discrepancy-based Search (PDDS) et Parallel Depth-First Search (PDFS). Les algorithmes parallèles ainsi obtenus créent un partage intrinsèque de la charge de travail : la différence de charge de travail entre les processeurs est bornée lorsqu'une branche de l'arbre de recherche est coupée. En utilisant des jeux de données de partenaires industriels, nous avons pu améliorer les meilleures solutions connues. Avec la deuxième approche, nous avons élaboré une méthode pour minimiser les changements effectués à un plan de production existant lorsque de nouvelles informations, telles que des commandes additionnelles, sont prises en compte. Replanifier entièrement les activités de production peut mener à l'obtention d'un plan de production très différent qui mène à des coûts additionnels et des pertes de temps pour les entreprises. Nous étudions les perturbations causéees par la replanification à l'aide de trois métriques de distances entre deux plans de production : la distance de Hamming, la distance d'édition et la distance de Damerau-Levenshtein. Nous proposons trois modèles mathématiques permettant de minimiser ces perturbations en incluant chacune de ces métriques comme fonction objectif au moment de la replanification. Nous appliquons cette approche au problème de planification et ordonnancement des opérations de finition du bois d'oeuvre et nous démontrons que cette approche est plus rapide qu'une replanification à l'aide du modèle d'origine.We study in this thesis two approaches that reduce the processing time needed to solve planning and ordering problems in a constraint programming context. We experiment with multiple thousands of processors on the planning and scheduling problem of wood-finish operations. These issues are of a great importance for businesses, because they can better manage their production and save costs related to their operations. The first approach consists in a parallelization of the problem solving algorithm. We propose a new parallelization technique (named PDS) of the search strategies, that reaches four goals: conservation of the nodes visit order in the search tree as defined by the sequential algorithm, balancing of the workload between the processors, robustness against hardware failures, and absence of communication between processors during the treatment. We apply this technique to parallelize the Limited Discrepancy-based (LDS) search strategy to obtain Parallel Limited Discrepancy-Based Search (PLDS). We then show that this technique can be generalized by parallelizing two other search strategies: Depth-Bounded discrepancy Search (DDS) and Depth-First Search (DFS). We obtain, respectively, Parallel Discrepancy-based Search (PDDS) and Parallel Depth-First Search (PDFS). The algorithms obtained this way create an intrinsic workload balance: the imbalance of the workload among the processors is bounded when a branch of the search tree is pruned. By using datasets coming from industrial partners, we are able to improve the best known solutions. With the second approach, we elaborated a method to minimize the changes done to an existing production plan when new information, such as additional orders, are taken into account. Completely re-planning the production activities can lead to a very different production plan which create additional costs and loss of time for businesses. We study the perturbations caused by the re-planification with three distance metrics: Hamming distance, Edit distance, and Damerau-Levenshtein Distance. We propose three mathematical models that allow to minimize these perturbations by including these metrics in the objective function when replanning. We apply this approach to the planning and scheduling problem of wood-finish operations and we demonstrate that this approach outperforms the use of the original model

실시간 근거리 영상화를 위한 MIMO 역합성 개구 레이더 시스템

학위논문(박사) -- 서울대학교대학원 : 공과대학 전기·정보공학부, 2022. 8. 남상욱.Microwave and millimeter wave (micro/mmW) imaging systems have advantages over other imaging systems in that they have penetration properties over non-metallic structures and non-ionization. However, these systems are commercially applicable in limited areas. Depending on the quality and size of the images, a system can be expensive and images cannot be provided in real-time. To overcome the challenges of the current micro/mmW imaging system, it is critical to suggest a new system concept and prove its potential benefits and hazards by demonstrating the testbed. This dissertation presents Ku1DMIC, a wide-band micro/mmW imaging system using Ku-band and 1D-MIMO array, which can overcome the challenges above. For cost-effective 3D imaging capabilities, Ku1DMIC uses 1D-MIMO array configuration and inverse synthetic aperture radar (ISAR) technique. At the same time, Ku1DMIC supports real-time data acquisition through a system-level design of a seamless interface with frequency modulated continuous wave (FMCW) radar. To show the feasibility of 3D imaging with Ku1DMIC and its real-time capabilities, an accelerated imaging algorithm, 1D-MIMO-ISAR RSA, is proposed and demonstrated. The detailed contributions of the dissertation are as follows. First, this dissertation presents Ku1DMIC – a Ku-band MIMO frequency-modulated continuous-wave (FMCW) radar experimental platform with real-time 2D near-field imaging capabilities. The proposed system uses Ku-band to cover the wider illumination area given the limited number of antennas and uses a fast ramp and wide-band FMCW waveform for rapid radar data acquisition while providing high-resolution images. The key design aspect behind the platform is stability, reconfigurability, and real-time capabilities, which allows investigating the exploration of the system’s strengths and weaknesses. To satisfy the design aspect, a digitally assisted platform is proposed and realized based on an AMD-Xilinx UltraScale+ Radio Frequency System on Chip (RFSoC). The experimental investigation for real-time 2D imaging has proved the ability of video-rate imaging at around 60 frames per second. Second, a waveform digital pre-distortion (DPD) method and calibration method are proposed to enhance the image quality. Even if a clean FMCW waveform is generated with the aid of the optimized waveform generator, the signal will inevitably suffer from distortion, especially in the RF subsystem of the platform. In near-field imaging applications, the waveform DPD is not effective at suppressing distortion in wide-band FMCW radar systems. To solve this issue, the LO-DPD architecture and binary search based DPD algorithm are proposed to make the waveform DPD effective in Ku1DMIC. Furthermore, an image-domain optimization correction method is proposed to compensate for the remaining errors that cannot be eliminated by the waveform DPD. For robustness to various unwanted signals such as noise and clutter signals, two regularized least squares problems are applied and compared: the generalized Tikhonov regularization and the total variation (TV) regularization. Through various 2D imaging experiments, it is confirmed that both methods can enhance the image quality by reducing the sidelobe level. Lastly, the research is conducted to realize real-time 3D imaging by applying the ISAR technique to Ku1DMIC. The realization of real-time 3D imaging using 1D-MIMO array configuration is impactful in that this configuration can significantly reduce the costs of the 3D imaging system and enable imaging of moving objects. To this end, the signal model for the 1D-MIMO-ISAR configuration is presented, and then the 1D-MIMO-ISAR range stacking algorithm (RSA) is proposed to accelerate the imaging reconstruction process. The proposed 1D-MIMO-ISAR RSA can reconstruct images within hundreds of milliseconds while maintaining almost the same image quality as the back-projection algorithm, bringing potential use for real-time 3D imaging. It also describes strategies for setting ROI, considering the real-world situations in which objects enter and exit the field of view, and allocating GPU memory. Extensive simulations and experiments have demonstrated the feasibility and potential benefits of 1D-MIMO-IASR configuration and 1D-MIMO-ISAR RSA.마이크로파 및 밀리미터파(micro/mmW) 영상화 시스템은 비금속 구조 및 비이온화에 비해 침투 특성이 있다는 점에서 다른 이미징 시스템에 비해 장점이 있다. 그러나 이러한 시스템은 제한된 영역에서만 상업적으로 적용되고 있다. 이미지의 품질과 크기에 따라 시스템이 매우 고가일 수 있으며 이미지를 실시간으로 제공할 수 없는 현황이다. 현재의 micro/mmW 이미징 시스템의 문제를 극복하려면 새로운 시스템 개념을 제안하고 테스트베드를 시연하여 잠재적인 이점과 위험을 입증하는 것이 중요하다. 본 논문에서는 Ku-band와 1D-MIMO 어레이를 이용한 광대역 micro/mmW 이미징 시스템인 Ku1DMIC를 제안하여 위와 같은 문제점을 극복할 수 있다. 비용 효율적인 3차원 영상화 기능을 위해 Ku1DMIC는 1D-MIMO 배열 기술과 ISAR(Inverse Synthetic Aperture Radar) 기술을 사용한다. 동시에 Ku1DMIC는 주파수 변조 연속파 (FMCW) 레이더와의 원활한 인터페이스의 시스템 수준 설계를 통해 실시간 데이터 수집을 지원한다. Ku1DMIC를 사용한 3차원 영상화의 구현 및 실시간 기능의 가능성을 보여주기 위해, 2차원 영상화를 위한 1D-MIMO RSA과 3차원 영상화를 위한 1D-MIMO-ISAR RSA가 제안되고 Ku1DMIC에서 구현된다. 따라서, 본 학위 논문의 주요 기여는 Ku-band 1D-MIMO 배열 기반 영상화 시스템 프로토타입을 개발 및 테스트하고, ISAR 기반 3차원 영상화 기능을 검사하고, 실시간 3차원 영상화 가능성을 조사하는 것이다. 이에 대한 세부적인 기여 항목은 다음과 같다. 첫째, 실시간 2D 근거리장 이미징 기능을 갖춘 Ku 대역 MIMO 주파수 변조 연속파(FMCW) 레이더 실험 플랫폼인 Ku1DMIC를 제시한다. 제안하는 시스템은 제한된 수의 안테나에서 더 넓은 조명 영역을 커버하기 위해 Ku 대역을 사용하고 고해상도 이미지를 제공하면서 빠른 레이더 데이터 수집을 위해 고속 램프 및 광대역 FMCW 파형을 사용한다. 플랫폼의 핵심 설계 원칙은 안정성, 재구성 가능성 및 실시간 기능으로 시스템의 강점과 약점을 광범위하게 탐색한다. 설계 원칙을 만족시키기 위해 AMD-Xilinx UltraScale+ RFSoC(Radio Frequency System on Chip)를 기반으로 디지털 지원 플랫폼을 제안하고 구현한다. 실시간 2D 이미징에 대한 실험적 조사는 초당 약 60프레임에서 비디오 속도 이미징의 능력을 입증했다. 둘째, 영상 품질 향상을 위한 파형 디지털 전치왜곡(DPD) 방법과 보정 방법을 제안한다. 최적화된 파형 발생기의 도움으로 깨끗한 FMCW 파형이 생성되더라도 특히 플랫폼의 RF 하위 시스템에서 신호는 필연적으로 왜곡을 겪게된다. 근거리 영상화 응용 분야에서는 파형 DPD는 광대역 FMCW 레이더 시스템의 왜곡을 억제하는 데 효과적이지 않다. 이 문제를 해결하기 위해 Ku1DMIC에서 파형 DPD가 유효하도록 LO-DPD 아키텍처와 이진 탐색 기반 DPD 알고리즘을 제안한다. 또한, 파형 DPD로 제거할 수 없는 나머지 오류를 보상하기 위해 이미지 영역 최적화 보정 방법을 제안한다. 노이즈 및 클러터 신호와 같은 다양한 원치 않는 신호에 대한 견고성을 위해 일반화된 Tikhonov 정규화 및 전체 변동(TV) 정규화라는 두 가지 정규화된 최소 자승 문제를 적용 후 비교한다. 다양한 2차원 영상화 실험을 통해 두 방법 모두 부엽 레벨을 줄여 화질을 향상시킬 수 있음을 확인한다. 마지막으로, ISAR 기법을 2차원 영상 플랫폼에 적용하여 실시간 3차원 영상을 구현하기 위한 연구를 진행한다. 1D-MIMO-ISAR 구성에서 실시간 3D 이미징의 구현은 이러한 구성이 3D 이미징 시스템의 비용을 크게 줄일 수 있다는 점에서 영향력이 있다. 따라서 이 논문에서는 1D-MIMO-ISAR 구성에 대한 이미징 재구성을 가속화하기 위해 1D-MIMO-ISAR 범위 스태킹 알고리즘(RSA)을 제안한다. 제안된 1D-MIMO-ISAR RSA는 널리 알려진 Back-Projection 알고리즘과 거의 동일한 이미지 품질을 유지하면서도 수백 밀리초 이내에 이미지를 재구성함으로써 실시간 영상화에 대한 가능성을 보여준다. 또한 물체가 시야에 들어오고 나가는 실제 상황을 고려하기 위한 ROI 설정, 그리고 메모리 할당에 대한 전략을 설명한다. 광범위한 시뮬레이션과 실험을 통해 1D-MIMO-IASR 구성 및 1D-MIMO-ISAR RSA의 가능성과 잠재적 이점을 확인한다.1 INTRODUCTION 1 1.1 Microwave and millimeter-wave imaging 1 1.2 Imaging with radar system 2 1.3 Challenges and motivation 5 1.4 Outline of the dissertation 8 2 FUNDAMENTAL OF TWO-DIMENSIONAL IMAGING USING A MIMO RADAR 9 2.1 Signal model 9 2.2 Consideration of waveform 12 2.3 Image reconstruction algorithm 16 2.3.1 Back-projection algorithm 16 2.3.2 1D-MIMO range-migration algorithm 20 2.3.3 1D-MIMO range stacking algorithm 27 2.4 Sampling criteria and resolution 31 2.5 Simulation results 36 3 MIMO-FMCW RADAR IMPLEMENTATION WITH 16 TX - 16 RX ONE- DIMENSIONAL ARRAYS 46 3.1 Wide-band FMCW waveform generator architecture 46 3.2 Overall system architecture 48 3.3 Antenna and RF transceiver module 53 3.4 Wide-band FMCW waveform generator 55 3.5 FPGA-based digital hardware design 63 3.6 System integration and software design 71 3.7 Testing and measurement 75 3.7.1 Chirp waveform measurement 75 3.7.2 Range profile measurement 77 3.7.3 2-D imaging test 79 4 METHODS OF IMAGE QUALITY ENHANCEMENT 84 4.1 Signal model 84 4.2 Digital pre-distortion of chirp signal 86 4.2.1 Proposed DPD hardware system 86 4.2.2 Proposed DPD algorithm 88 4.2.3 Measurement results 90 4.3 Robust calibration method for signal distortion 97 4.3.1 Signal model 98 4.3.2 Problem formulation 99 4.3.3 Measurement results 105 5 THREE-DIMENSIONAL IMAGING USING 1-D ARRAY SYSTEM AND ISAR TECHNIQUE 110 5.1 Formulation for 1D-MIMO-ISAR RSA 111 5.2 Algorithm implementation 114 5.3 Simulation results 120 5.4 Experimental results 122 6 CONCLUSIONS AND FUTURE WORK 127 6.1 Conclusions 127 6.2 Future work 129 6.2.1 Effects of antenna polarization in the Ku-band 129 6.2.2 Forward-looking near-field ISAR configuration 130 6.2.3 Estimation of the movement errors in ISAR configuration 131 Abstract (In Korean) 145 Acknowlegement 148박

Anytime Algorithms for ROBDD Symmetry Detection and Approximation

Reduced Ordered Binary Decision Diagrams (ROBDDs) provide a dense and memory efficient representation of Boolean functions. When ROBDDs are applied in logic synthesis, the problem arises of detecting both classical and generalised symmetries. State-of-the-art in symmetry detection is represented by Mishchenko's algorithm. Mishchenko showed how to detect symmetries in ROBDDs without the need for checking equivalence of all co-factor pairs. This work resulted in a practical algorithm for detecting all classical symmetries in an ROBDD in O(|G|3) set operations where |G| is the number of nodes in the ROBDD. Mishchenko and his colleagues subsequently extended the algorithm to find generalised symmetries. The extended algorithm retains the same asymptotic complexity for each type of generalised symmetry. Both the classical and generalised symmetry detection algorithms are monolithic in the sense that they only return a meaningful answer when they are left to run to completion. In this thesis we present efficient anytime algorithms for detecting both classical and generalised symmetries, that output pairs of symmetric variables until a prescribed time bound is exceeded. These anytime algorithms are complete in that given sufficient time they are guaranteed to find all symmetric pairs. Theoretically these algorithms reside in O(n3+n|G|+|G|3) and O(n3+n2|G|+|G|3) respectively, where n is the number of variables, so that in practice the advantage of anytime generality is not gained at the expense of efficiency. In fact, the anytime approach requires only very modest data structure support and offers unique opportunities for optimisation so the resulting algorithms are very efficient. The thesis continues by considering another class of anytime algorithms for ROBDDs that is motivated by the dearth of work on approximating ROBDDs. The need for approximation arises because many ROBDD operations result in an ROBDD whose size is quadratic in the size of the inputs. Furthermore, if ROBDDs are used in abstract interpretation, the running time of the analysis is related not only to the complexity of the individual ROBDD operations but also the number of operations applied. The number of operations is, in turn, constrained by the number of times a Boolean function can be weakened before stability is achieved. This thesis proposes a widening that can be used to both constrain the size of an ROBDD and also ensure that the number of times that it is weakened is bounded by some given constant. The widening can be used to either systematically approximate an ROBDD from above (i.e. derive a weaker function) or below (i.e. infer a stronger function). The thesis also considers how randomised techniques may be deployed to improve the speed of computing an approximation by avoiding potentially expensive ROBDD manipulation

Measurements, Models, Systems and Design

531 s.

Recent Trends in Communication Networks

In recent years there has been many developments in communication technology. This has greatly enhanced the computing power of small handheld resource-constrained mobile devices. Different generations of communication technology have evolved. This had led to new research for communication of large volumes of data in different transmission media and the design of different communication protocols. Another direction of research concerns the secure and error-free communication between the sender and receiver despite the risk of the presence of an eavesdropper. For the communication requirement of a huge amount of multimedia streaming data, a lot of research has been carried out in the design of proper overlay networks. The book addresses new research techniques that have evolved to handle these challenges

The use of molecular dynamics simulation for the study of polymeric and lipid based drug delivery systems

Systemic administration is the conventional method for administrating drugs. Following injection, ideally, we wish the drug only to locate to the target tissue, however, this is not what occurs; the drug molecules rather distribute throughout the entire body via the blood stream. Regarding some drugs, in particular chemotherapy agents, this often leads to severe dose limiting side effects and unsatisfactory therapeutic results. On the other hand, many drugs as is also the case for the chemotherapy agents, demonstrate low aqueous solubility and suboptimal pharmacokinetic properties. These problems all necessitate the use of drug delivery systems (DDSs) as they decrease the side effects of drugs while also improving drug bioavailability and pharmacokinetics. Although there are different varieties of DDSs, we have focused on those categorized as polymeric or lipidic. Depending on the drug to be delivered and site of action of the drug, polymeric DDSs can be used either locally or systemically. Hydrogels and electrospun polymer fibers are two examples of polymeric DDSs that are used for the local delivery of many drugs, including antibiotics and anticancer drugs. The other form of polymeric DDSs are nanoparticles that are capable of carrying and in some cases targeting drug molecules. These polymeric DDSs are generally injected into the blood stream to reach their target site. Lipidic DDSs mainly are used in the form of nanoparticles that, depending on their lipid composition and method of preparation, would have different characteristics. Liposomes and solid lipid nanoparticles are two examples of lipidic DDSs. Despite the huge number of publications regarding the use of nanoparticles as DDSs, the number of approved drug therapies that make use of nanoparticle-based delivery systems still remains small. One of the reasons for this problem is that formulations of DDSs are complicated and difficult to optimize. Drug delivery systems should be further redesigned and optimized, however, this has proved challenging due to intrinsic and practical experimental limitations. For example, it is difficult to experimentally elucidate the reason many DDSs show promise in vitro but fail in vivo. The limitations to the extent to which mechanistic insight can be gained from experiments regarding DDSs can be compensated by computational molecular modelling techniques that provide detailed information on molecular interactions of drugs and carriers. The insights obtained by the studies performed in this thesis can be used to improve the design of DDSs. In this thesis, two polymeric (studies I and IV) and two lipidic (studies II and III) DDSs were studied by all-atom molecular dynamics (MD) simulations. In each of these studies, a specific property of the DDS was evaluated in detail. These properties are drug release profile (study I), stability (study II), pH-sensitivity (study III) and size (study IV). We evaluated these properties through investigation of the three varieties of interactions DDSs have: interactions of DDSs with the loaded drug, interactions among the components of DDSs and interactions between the DDSs and the medium, namely water and ions. While it is difficult to directly determine an accurate picture of these interactions experimentally at atomic scale resolution, all- atom MD simulation can provide insight into this.Lääkeaineet annostellaan yleensä systeemisesti ja olisi ideaalista, että annostelun jälkeen lääkeaine vaikuttaisi vain paikallisesti kohdekudoksessa. Käytännössä näin ei kuitenkaan tapahdu, vaan pikemminkin lääkeainemolekyylit jakautuvat koko kehoon verenkierron mukana. Joidenkin lääkkeiden, erityisesti kemoterapeuttisten aineiden kohdalla, tämä johtaa usein vakaviin annosta rajoittaviin sivuvaikutuksiin ja näin ollen epätyydyttäviin terapeuttisiin tuloksiin. Toisaalta monilla lääkkeillä, kuten myös kemoterapia-aineilla, on myös alhainen vesiliukoisuus ja huonot farmakokineettiset ominaisuudet. Kaikki nämä ongelmat edellyttävät erilaisten lääkekuljetusjärjestelmien käyttöä, koska ne vähentävät esimerkiksi haitallisia sivuvaikutuksia ja parantavat lääkeaineiden biologista hyötyosuutta. Vaikka lääkekuljetusjärjestelmiä on erilaisia, olemme keskittyneet tässä väitöskirjassa vain niihin, jotka on luokiteltu polymeeri- tai lipidipohjaisiksi. Kuljetettavasta lääkeaineesta ja lääkkeen vaikutuspaikasta riippuen polymeeripohjaisia lääkekuljetusjärjestelmiä voidaan käyttää paikallisesti tai systeemisesti. Hydrogeelit ja sähkökehrätyt polymeerikalvot ovat esimerkkejä tällaisista lääkekuljetusjärjestelmistä ja niitä käytetään monien lääkkeiden, kuten antibioottien ja syöpälääkkeiden paikalliseen annosteluun. Polymeeripohjaiset nanohiukkaset pystyvät vuorostaan kuljettamaan ja joissakin tapauksissa myös kohdentamaan lääkeainemolekyylejä. Nanohiukkaset ruiskutetaan yleensä suoraan verenkiertoon, jotta ne saavuttaisivat terapeuttisen kohteen. Lipideistä koostuvat lääkekuljetusjärjestelmät ovat pääasiassa nanohiukkasia, joilla on lipidikoostumuksesta ja valmistusmenetelmästä johtuen erilaisia ominaisuuksia. Liposomit ja kiinteät lipidinanohiukkaset ovat esimerkkejä lääkeaineiden kuljetusjärjestelmistä, jotka pohjautuvat rasva-aineisiin eli lipideihin. Siitä huolimatta, että kirjallisuudesta löytyy valtava määrä tieteellisiä julkaisuja, jotka liittyvät nanohiukkasten käyttöön lääkekuljetusjärjestelminä, hyväksyttyjen nanohiukkaspohjaisten lääkehoitomuotojen määrä on edelleen pieni. Tämä johtuu siitä, että valmisteet ovat monimutkaisia, vaikeasti optimoitavissa. Nanohiukkasia tulisi edelleen suunnitella ja optimoida, mutta tämä on osoittautunut haastavaksi mittalaitteiden rajoituksien vuoksi. Esimerkiksi on erittäin vaikeaa selvittää kokeellisesti, miksi monet nanohiukkaset ovat lupaavia in vitro mittauksissa, mutta epäonnistuvat in vivo kokeissa. Kokeellisia mittauksia, joissa nanohiukkasista saadaan mekanistista tietoa, voidaan kompensoida erilaisilla in silico molekyylimallinnustekniikoilla, jotka tarjoavat yksityiskohtaista tietoa lääkeaineiden ja kantajien molekyylivuorovaikutuksista. Väitöskirjassa esitettyjä tuloksia voidaan hyödyntää lääkeaineiden kuljetusjärjestelmien suunnittelussa. Tässä väitöskirjassa tutkittiin kahta polymeereistä (tutkimukset I ja IV) ja kahta lipideistä (tutkimukset II ja III) koostuvaa lääkekuljetusjärjestelmää hyödyntäen atomistisia molekyylidynamiikka simulaatioita. Jokaisessa tutkimuksessa lääkekuljetusjärjestelmän tietty ominaisuus arvioitiin yksityiskohtaisesti. Näitä ominaisuuksia olivat lääkeaineen vapautumisprofiili (tutkimus I), stabiilius (tutkimus II), pH-herkkyys (tutkimus III) ja koko (tutkimus IV). Arvioimme näitä ominaisuuksia tutkimalla kolmea erilaista vuorovaikutusta lääkekuljetusjärjestelmissä: matriisin vuorovaikutus ladatun lääkkeen kanssa, matriisin eri komponenttien vuorovaikutus keskenään sekä vuorovaikutus lääkekuljetusjärjestelmän ja väliaineen (vesi ja ionit) välillä. Siitä huolimatta, että kokeellisilla mittauksilla on erittäin vaikeaa tuottaa atomitason kuva näistä vuorovaikutuksista, voidaan näistä saada laskennallisia molekyylidynamiikkasimulaatioita hyödyntäen hyvä käsitys

Design and optimization for wireless-powered networks

Wireless Power Transfer (WPT) opens an emerging area of Wireless-Powered Networks (WPNs). In narrowband WPNs, beamforming is recognized as a key technique for enhancing information and energy transfer. However, in multi-antenna multi-sine WPT systems, not only the beamforming gain but also the rectifier nonlinearity can be exploited by a waveform design to boost the end-to-end power transfer efficiency. This thesis proposes and optimizes novel transmission strategies for two types of WPNs: narrowband autonomous relay networks and multi-antenna multi-sine WPT systems. The thesis starts by proposing a novel Energy Flow-Assisted (EFA) relaying strategy for a one-way multi-antenna Amplify-and-Forward (AF) autonomous relay network. In contrast to state-of-the-art autonomous relaying strategies, the EFA enables the relay to simultaneously harvest power from source information signals and a dedicated Energy Flow (EF) from the destination for forwarding. As a baseline, a Non-EFA (NEFA) strategy, where the relay splits power from the source signals, is also investigated. We optimize relay strategies for EFA and NEFA, so as to maximize the end-to-end rate and gain insights into the benefit of the EF. To transmit multiple data streams, we extend the EFA and the NEFA to a Multiple-Input Multiple-Output (MIMO) relay network. A novel iterative algorithm is developed to jointly optimize source precoders and relay matrices for the EFA and the NEFA, in order to maximize the end-to-end rate. Based on a channel diagonalization method, we also propose less complex EFA and NEFA algorithms. In the study of waveform designs for multi-antenna multi-sine WPT, large-scale designs with many sinewaves and transmit antennas, computationally tractable algorithms and optimal multiuser waveforms remain open challenges. To tackle these issues, we propose efficient waveform optimization algorithms to maximize the multiuser weighted-sum/minimum rectenna DC output voltage, assuming perfect Channel State Information at the Transmitter (CSIT). An optimization framework is developed to derive these waveform algorithms. Relaxing the assumption on CSIT, we propose waveform strategies for multi-antenna multi-sine WPT based on waveform selection (WS) and waveform refinement (WR), respectively. Applying the strategies, an energy transmitter can generate preferred waveforms for WPT from predesigned codebooks of waveform precoders, according to limited feedback from an energy receiver, which carries information on the harvested energy. Although the WR-based strategy is suboptimal for maximizing the average rectenna output voltage, it causes a lower overhead than the WS-based strategy. We propose novel algorithms to optimize the codebooks for the two strategies.Open Acces

Effective integrations of constraint programming, integer programming and local search for two combinatorial optimisation problems

This thesis focuses on the construction of effective and efficient hybrid methods based on the integrations of Constraint Programming (CP), Integer Programming (IP) and local search (LS) to tackle two combinatorial optimisation problems from different application areas: the nurse rostering problems and the portfolio selection problems. The principle of designing hybrid methods in this thesis can be described as: for the combinatorial problems to be solved, the properties of the problems are investigated firstly and the problems are decomposed accordingly in certain ways; then the suitable solution techniques are integrated to solve the problem based on the properties of substructures/subproblems by taking the advantage of each technique. For the over-constrained nurse rostering problems with a large set of complex constraints, the problems are first decomposed by constraint. That is, only certain selected set of constraints is considered to generate feasible solutions at the first stage. Then the rest of constraints are tackled by a second stage local search method. Therefore, the hybrid methods based on this constraint decomposition can be represented by a two-stage framework “feasible solution + improvement”. Two integration methods are proposed and investigated under this framework. In the first integration method, namely a hybrid CP with Variable Neighourhood Search (VNS) approach, the generation of feasible initial solutions relies on the CP while the improvement of initial solutions is gained by a simple VNS in the second stage. In the second integration method, namely a constraint-directed local search, the local search is enhanced by using the information of constraints. The experimental results demonstrate the effectiveness of these hybrid approaches. Based on another decomposition method, Dantzig-Wolfe decomposition, in the third integration method, a CP based column generation, integrates the feasibility reasoning of CP with the relaxation and optimality reasoning of Linear Programming. The experimental results demonstrate the effectiveness of the methods as well as the knowledge of the quality of the solution. For the portfolio selection problems, two integration methods, which integrate Branch-and-Bound algorithm with heuristic search, are proposed and investigated. In layered Branch-and-Bound algorithm, the problem is decomposed into the subsets of variables which are considered at certain layers in the search tree according to their different features. Node selection heuristics, and branching rules, etc. are tailored to the individual layers, which speed up the search to the optimal solution in a given time limit. In local search branching Branch-and-Bound algorithm, the idea of local search is applied as the branching rule of Branch-and-Bound. The local search branching is applied to generate a sequence of subproblems. The procedure for solving these subproblems is accelerated by means of the solution information reusing. This close integration between local search and Branch-and-Bound improves the efficiency of the Branch-and-Bound algorithm according to the experimental results. The hybrid approaches benefit from each component which is selected according to the properties of the decomposed problems. The effectiveness and efficiency of all the hybrid approaches to the two application problems developed in this thesis are demonstrated. The idea of designing appropriate components in hybrid approach concerning properties of subproblems is a promising methodology with extensive potential applications in other real-world combinatorial optimisation problems