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A surveyonheuristics for the two-dimensional rectangular strip packing problem
Get PDFTwo-dimensional rectangular strip packing problems belong to the broader class of Cutting and Packing (C&P) problems, in which small items are required to be cut from or packed on a larger object, so that the waste (unused regions of the large object) is minimized. C&P problems differ from other combinatorial optimization problems by the intrinsic geometric constraints: items may not overlap and have to be fully contained in the large object. This survey approaches the specific C&P problem in which all items are rectangles, therefore fully characterized by a width and a height, and the large object is a strip, i.e. a rectangle with a fixed width but an infinite height, being the problem’s goal to place all rectangles on the strip so that the height is minimized. These problems have been intensively and extensively tackled in the literature and this paper will focus on heuristic resolution methods. Both the seminal and the most recent approaches (from the last decade) will be reviewed, in a rather tutorial flavor, and classified according to their type: constructive heuristics, improvement heuristics with search over sequences and improvement heuristics with search over layouts. Building on this review, research gaps are identified and the most interesting research directions pointed out. © 2016 Brazilian Operations Research Society
Mining multi-dimensional concept-drifting data streams using Bayesian network classifiers
Get PDFIn recent years, a plethora of approaches have been proposed to deal with the increasingly challenging task of mining concept-drifting data streams. However, most of these approaches can only be applied to uni-dimensional classification problems where each input instance has to be assigned to a single output class variable. The problem of mining multi-dimensional data streams, which includes multiple output class variables, is largely unexplored and only few streaming multi-dimensional approaches have been recently introduced. In this paper, we propose a novel adaptive method, named Locally Adaptive-MB-MBC (LA-MB-MBC), for mining streaming multi-dimensional data. To this end, we make use of multi-dimensional Bayesian network classifiers (MBCs) as models. Basically, LA-MB-MBC monitors the concept drift over time using the average log-likelihood score and the Page-Hinkley test. Then, if a concept drift is detected, LA-MB-MBC adapts the current MBC network locally around each changed node. An experimental study carried out using synthetic multi-dimensional data streams shows the merits of the proposed method in terms of concept drift detection as well as classification performance
Defining the Best distribution Network for Grocery Retail Stores
No full textLarge food retailers have to deal with a complex distribution network with multiple distribution centres, different temperature requirements, and a vast range of store formats. This project used an optimization-simulation approach to help food retailer Sonae MC make the best decisions regarding product-warehouse-outlet assignment, product delivery modes planning and fleet sizing
Optical fibers as beam shapers: from Gaussian beams to optical vortices
Get PDFThis Letter reports a new method for the generation of optical vortices using a micropatterned optical fiber tip. Here, a spiral phase plate (2 pi phase shift) is micromachined on the tip of an optical fiber using a focused ion beam. This is a high resolution method that allows milling the fibers with nanoscale resolution. The plate acts as a beam tailoring system, transforming the fundamental guided mode, specifically a Gaussian mode, into the Laguerre-Gaussian mode (LG(01)), which carries orbital angular momentum. The experimental results are supported by computational simulations based on the finite-difference time-domain method. (C) 2016 Optical Society of Americ
Evaluating the influence of skipper skills in the performance of Portuguese artisanal dredge vessels
No full textIt is widely recognized that skippers can have a significant role in their vessel performance levels. However, in many studies that seek to address differences in performance of vessels, the contribution of the skipper is often not quantified, or the influencing factors are not explained. This study examines the effect of social factors, such as family heritage, education and professional expertise, on skipper skill and the economic performance of the Portuguese artisanal dredge fleet. This is done using a stochastic production frontier model and data on the weekly activity of 54 vessels operating during 2013 and 2014. The results suggest that in this fishery age and education levels of skippers are important determinants of efficiency. Experience as a skipper was no determinant of performance, possibly due to the simplicity of the technical equipment onboard. From a managerial perspective, this indicates that local authorities should consider initiatives to enhance the education levels and professional training of skippers, if they aim to improve the effectiveness of artisanal fleets
Simultaneous measurement of temperature and refractive index using focused ion beam milled Fabry-Perot cavities in optical fiber micro-tips
Get PDFOptical fiber micro-tips are promising devices for sensing applications in small volume and difficult to access locations, such as biological and biomedical settings. The tapered fiber tips are prepared by dynamic chemical etching, reducing the size from 125 mu m to just a few mu m. Focused ion beam milling is then used to create cavity structures on the tapered fiber tips. Two different Fabry-Perot micro-cavities have been prepared and characterized: a solid silica cavity created by milling two thin slots and a gap cavity. A third multi-cavity structure is fabricated by combining the concepts of solid silica cavity and gap cavity. This micro-tip structure is analyzed using a fast Fourier transform method to demultiplex the signals of each cavity. Simultaneous measurement of temperature and external refractive index is then demonstrated, presenting sensitivities of 15.8 pm/K and -1316 nm/RIU, respectively. (C) 2016 Optical Society of Americ
iDEAS: A web-based system for dry eye assessment
No full textBackground and objectives: Dry eye disease is a public health problem, whose multifactorial etiology challenges clinicians and researchers making necessary the collaboration between different experts and centers. The evaluation of the interference patterns observed in the tear film lipid layer is a common clinical test used for dry eye diagnosis. However, it is a time-consuming task with a high degree of intra- as well as inter-observer variability, which makes the use of a computer-based analysis system highly desirable. This work introduces iDEAS (Dry Eye Assessment System), a web-based application to support dry eye diagnosis. Methods: iDEAS provides a framework for eye care experts to collaboratively work using image-based services in a distributed environment. It is composed of three main components: the web client for user interaction, the web application server for request processing, and the service module for image analysis. Specifically, this manuscript presents two automatic services: tear film classification, which classifies an image into one interference pattern; and tear film map, which illustrates the distribution of the patterns over the entire tear film. Results: iDEAS has been evaluated by specialists from different institutions to test its performance. Both services have been evaluated in terms of a set of performance metrics using the annotations of different experts. Note that the processing time of both services has been also measured for efficiency purposes. Conclusions: iDEAS is a web-based application which provides a fast, reliable environment for dry eye assessment. The system allows practitioners to share images, clinical information and automatic assessments between remote computers. Additionally, it save time for experts, diminish the inter-expert variability and can be used in both clinical and research settings. © 2016 Elsevier Ireland Ltd
ICT-based solution approach for collaborative delivery of customised products
Get PDFGrowing interest on business collaboration motivates today's industries, especially small and medium enterprises (SMEs) to establish and manage dynamic and non-hierarchical business networks to respond to market opportunities with added business benefits. This business environment requires concurrent work and real-time information sharing between key business partners in order to design and develop customised products. The use of traditional communication media such as e-mail, phone and fax is not satisfactory to get real-time information and is time-consuming and most often ineffective. In such environments, an Information and Communication Technology (ICT)/Web-based technology supports real-time information sharing among networked SMEs for the collaborative design and manufacturing of customised products. This study proposes an innovative ICT platform supporting SMEs collaboration, through Web and the Internet of Things technologies, which follows the Net-Challenge conceptual approach and methodological guidelines for SMEs to form and operate virtual organisations for the collaborative development and delivery of customised products. The ICT Platform was assessed in three different industry domains, namely the textile and apparel, the footwear and the machine tools, respectively. This ICT solution promotes collaboration, with substantial advantages for SMEs including the reduction of costs and delivery time and improvement of the innovation potential