改进区域划分的圆Packing变分算法

通过改进基于Power图的区域划分,提出一种收敛速度更快的圆packing算法.首先固定容器面积,将输入圆缩小一定的倍数,随机撒在容器中;之后对圆心点进行三角化,并根据相邻圆的半径比值对容器进行区域划分;再让所有圆在不超出自己区域边界的条件下尽量等比例增长至最大;最后将划分区域-长大的过程迭代下去,得到最大增长倍数.实验结果表明,该算法能够使得圆packing的过程更快地达到收敛.国家自然科学基金(61472332);;福建省自然科学基金(2018J01104

An anytime tree search algorithm for two-dimensional two- and three-staged guillotine packing problems

[libralesso_anytime_2020] proposed an anytime tree search algorithm for the 2018 ROADEF/EURO challenge glass cutting problem (https://www.roadef.org/challenge/2018/en/index.php). The resulting program was ranked first among 64 participants. In this article, we generalize it and show that it is not only effective for the specific problem it was originally designed for, but is also very competitive and even returns state-of-the-art solutions on a large variety of Cutting and Packing problems from the literature. We adapted the algorithm for two-dimensional Bin Packing, Multiple Knapsack, and Strip Packing Problems, with two- or three-staged exact or non-exact guillotine cuts, the orientation of the first cut being imposed or not, and with or without item rotation. The combination of efficiency, ability to provide good solutions fast, simplicity and versatility makes it particularly suited for industrial applications, which require quickly developing algorithms implementing several business-specific constraints. The algorithm is implemented in a new software package called PackingSolver

The sensor based manipulation of irregularly shaped objects with special application to the semiconductor industry

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1998.Includes bibliographical references (leaves 91-94).by Vivek Anand Sujan.S.M

DRLMA: An Intelligent Move Acceptance for Combinatorial Optimization Problems based on Deep Reinforcement Learning

Numerous heuristic solution methods have been developed to tackle combinatorial opti- mization problems, often customized for specific problem domains and use-cases where they exhibit remarkable performance. However, their effectiveness diminishes significantly when applied to problem domains for which they were not originally designed, showcasing poor generalization capabilities. In contrast, metaheuristics are higher-level heuristics so- lution methods that aim to be applicable to a wide range of different problems. Perturba- tive metaheuristics operate by traversing the solution space through iterative application of modifications induced by low-level heuristics. This process continues until a specified stopping criteria is met, enabling the method to efficiently explore and refine solutions. A central aspect of these search-based methods is the move acceptance scheme, which determines whether or not the suggested modification is to be applied. The Simulated Annealing acceptance criteria, for instance, occasionally accepts uphill moves, or worse so- lutions, in order to explore the space of solutions and help the search escape local optima. In this thesis we propose Deep Reinforcement Learning Move Acceptance (DRLMA), a general move acceptance framework that leverages Deep Reinforcement Learning into the acceptance decision. A Deep RL agent is trained using problem-independent search information, enabling it to learn high-level acceptance strategies regardless of the specific combinatorial optimization problem at hand. We show that by replacing the Simulated Annealing acceptance criteria with DRLMA in two different heuristic selection frame- works, namely Adaptive Large Neighborhood Search (ALNS) and Deep Reinforcement Learning Hyperheuristic (DRLH), we are generally able to improve the performance of the respective search methods, the degree of improvement ranging from only slightly in the worst cases to considerably in the best cases.Masteroppgave i informatikkINF399MAMN-INFMAMN-PRO

Identification of the restrictive layer depth of cranberry soil

La canneberge est l'un des produits agricoles les plus importants du Canada sur le plan économique. Ce fruit est planté dans des champs construits à partir d'une couche de sol sableux au-dessus du profil de sol naturel du site. Le fruit obtient son eau requise principalement par subirrigation via le système de drainage souterrain. Les cycles d'irrigation et de drainage répétitifs conduisent au mouvement et à la migration de fines particules et induisent la consolidation de couches de sol et le blocage des vides interstitiels et des voies de transfert de fluides. Ce phénomène se traduit par une dégradation des sols entraînant des pertes de revenus. Les pertes seraient liées à la dégradation du sol et aussi au rendement des fruits au champ. Afin de prévenir ou de ralentir ce phénomène, certaines mesures de mitigation doivent être retenues: l'optimisation de la gestion des ressources en eau, le choix des espèces de canneberges plantées dans les champs et l'examen des caractéristiques physiques du sol utilisé dans construction des nouveaux champs. La canneberge est connue comme une plante qui nécessite une énorme quantité d'eau pour sa production (irrigation pour la croissance et la protection contre le gel, ennoiement des champs pour la récolte et la glaciation pour l'apport en sable); en revanche, la plante est sensible aux situations de mauvais drainage. Plusieurs études ont été menées pour examiner ces questions. Dans ce projet de doctorat, notre objectif était d'étudier le comportement du sol en faisant les suivis de la migration de particules fines, la consolidation de ce dernier et la formation de couches restrictives pour différents types de champs de canneberges. Pour atteindre cet objectif, nous avons utilisé la tomographie aux rayons X et développé une approche adaptative pour examiner les images et les données expérimentales de nos colonnes de sol. Les résultats du projet montrent comment le mouvement de l'eau influe la migration des particules fines et conduit à des modifications du profil de sol; entraînant la construction d'une couche hydraulique restrictive dans chacun des échantillons sous différentes conditions d'altérations du cycle d'irrigation/drainage au fil du temps. L'ensemble des examens et résultats obtenus nous a permis de dégager une vision de la détection du comportement du sol et des transformations de son profil de futurs champs de canneberges. La réalisation de cette étude permettra de conscientiser les producteurs de canneberges à l'évolution des profils des sols et à les guider dans leur sélection du type de sol à utiliser lors de la construction de nouveaux champs de canneberges. Le tout contribuera à augmenter la durée de vie de ces nouveaux champs de canneberges.Cranberry is economically one of the most important agricultural products of Canada. This fruit is commercially planted in fields constructed from a layer of sandy soil on top of the site's natural soil profile. The fruit accesses water mainly by subirrigation. Subirrigation and repetitive irrigation and drainage cycles lead to movement and migration of fine soil particles and induce consolidation of soil layers; blocking pore throats and fluid ways. This phenomenon results in soil degradation; leading to substantial losses of fruit yields and revenues. To prevent economic losses and decelerate soil degradation, some alternatives measures need to be considered, for example: optimization of water resources management, selection of specific species of cranberry and selection of proper soil types. Cranberry is known as a plant requiring huge amounts of water (irrigation for growth and frost protection, flooding for harvest and icing for sand application). On the other hand, the plant is sensitive to poor drainage conditions. Several studies have been conducted to examine these issues. In this PhD project, we studied soil behavior and examined migration of fine soil particles, soil consolidation and formation of restrictive layers of soil in different types of cranberry fields. To achieve this goal, we used x-ray tomography and developed an adaptive approach to examine the ensuing images and soil matric potential data from experimental soil columns. The results show how water movement impacts the migration of fine particles and leads to modifications of the soil profile resulting in the establishment of hydraulic restrictive layers under several alterations of the soil irrigation/drainage cycle. All these investigations and ensuing results have provided us an opportunity to build a framework on how to detect and anticipate the behavior of soils of future cranberry fields. The results of this study will help cranberry growers to understand the dynamics of soil profiles and guide them in the selection of the soil type to be used in the construction of new cranberry fields. In the end, the main outcome will increase the life span of future cranberry fields

New Methods for Motion Management During Radiation Therapy

In this thesis, a number of new image-based techniques for the management of intrafractional motion during radiation therapy are presented. Intra-fractional motion describes all kinds of anatomy changes - most prominently respiration - that occur during a single treatment session. Spatially confining the radiation dose to the tumour tissue and thus sparing surrounding healthy tissue is assumed to be crucial for a successful treatment with limited side effects. Unfortunately, the delivery of dose distributions that are sharply confined to the tumour is greatly complicated by patient motion. If not accounted for, this motion will lead to a smearing out of the original dose distribution and will facilitate the redistribution of dose from tumour to healthy tissue. Possible technical solutions for this issue include the interruption of the radiation delivery if the tumour leaves a predefined spatial ‘window’, and the reshaping of the treatment field ‘on-the-fly’ to follow the tumour. Regardless of which delivery techniques is selected, the patient motion needs to be reliably detected in real-time to allow for an adaptation of the treatment delivery. First, we present experimental results for a novel x-ray imaging system that is attached to the treatment delivery device and enables us to continuously monitor the tumour motion during treatment delivery with sub-mm accuracy, a latency better than 90 ms, and a 7 Hz update rate. Second, we present a Monte Carlo simulation for an improved amorphous-silicon flat-panel detector that reduced treatment beam filtration by 60% and long-range MV-scatter by 80%. We conclude this thesis by presenting results of an experimental demonstration of a novel dose-saving actively-triggered 4d cone-beam computed tomography device

The Fifth NASA Symposium on VLSI Design

The fifth annual NASA Symposium on VLSI Design had 13 sessions including Radiation Effects, Architectures, Mixed Signal, Design Techniques, Fault Testing, Synthesis, Signal Processing, and other Featured Presentations. The symposium provides insights into developments in VLSI and digital systems which can be used to increase data systems performance. The presentations share insights into next generation advances that will serve as a basis for future VLSI design

Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS 1994), volume 1

The AIAA/NASA Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS '94) was originally proposed because of the strong belief that America's problems of global economic competitiveness and job creation and preservation can partly be solved by the use of intelligent robotics, which are also required for human space exploration missions. Individual sessions addressed nuclear industry, agile manufacturing, security/building monitoring, on-orbit applications, vision and sensing technologies, situated control and low-level control, robotic systems architecture, environmental restoration and waste management, robotic remanufacturing, and healthcare applications