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This book presents the latest findings on one of the most intensely investigated subjects in computational mathematics--the traveling salesman problem. It sounds simple enough: given a set of cities and the cost of travel between each pair of them, the problem challenges you to find the cheapest route by which to visit all the cities and return home to where you began. Though seemingly modest, this exercise has inspired studies by mathematicians, chemists, and physicists. Teachers use it in the classroom. It has practical applications in genetics, telecommunications, and neuroscience. The authors of this book are the same pioneers who for nearly two decades have led the investigation into the traveling salesman problem. They have derived solutions to almost eighty-six thousand cities, yet a general solution to the problem has yet to be discovered. Here they describe the method and computer code they used to solve a broad range of large-scale problems, and along the way they demonstrate the interplay of applied mathematics with increasingly powerful computing platforms. They also give the fascinating history of the problem--how it developed, and why it continues to intrigue us.
Traveling salesman problem. --- TSP (Traveling salesman problem) --- Combinatorial optimization --- Graph theory --- Vehicle routing problem --- AT&T Labs. --- Accuracy and precision. --- Addition. --- Algorithm. --- Analysis of algorithms. --- Applied mathematics. --- Approximation algorithm. --- Approximation. --- Basic solution (linear programming). --- Best, worst and average case. --- Bifurcation theory. --- Big O notation. --- CPLEX. --- CPU time. --- Calculation. --- Chaos theory. --- Column generation. --- Combinatorial optimization. --- Computation. --- Computational resource. --- Computer. --- Connected component (graph theory). --- Connectivity (graph theory). --- Convex hull. --- Cutting-plane method. --- Delaunay triangulation. --- Determinism. --- Disjoint sets. --- Dynamic programming. --- Ear decomposition. --- Engineering. --- Enumeration. --- Equation. --- Estimation. --- Euclidean distance. --- Euclidean space. --- Family of sets. --- For loop. --- Genetic algorithm. --- George Dantzig. --- Georgia Institute of Technology. --- Greedy algorithm. --- Hamiltonian path. --- Hospitality. --- Hypergraph. --- Implementation. --- Instance (computer science). --- Institute. --- Integer. --- Iteration. --- Linear inequality. --- Linear programming. --- Mathematical optimization. --- Mathematics. --- Model of computation. --- Neuroscience. --- Notation. --- Operations research. --- Optimization problem. --- Order by. --- Pairwise. --- Parameter (computer programming). --- Parity (mathematics). --- Percentage. --- Polyhedron. --- Polytope. --- Pricing. --- Princeton University. --- Processing (programming language). --- Project. --- Quantity. --- Reduced cost. --- Requirement. --- Result. --- Rice University. --- Rutgers University. --- Scientific notation. --- Search algorithm. --- Search tree. --- Self-similarity. --- Simplex algorithm. --- Solution set. --- Solver. --- Source code. --- Special case. --- Stochastic. --- Subroutine. --- Subsequence. --- Subset. --- Summation. --- Test set. --- Theorem. --- Theory. --- Time complexity. --- Trade-off. --- Travelling salesman problem. --- Tree (data structure). --- Upper and lower bounds. --- Variable (computer science). --- Variable (mathematics).
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In the last few decades, near-infrared (NIR) spectroscopy has distinguished itself as one of the most rapidly advancing spectroscopic techniques. Mainly known as an analytical tool useful for sample characterization and content quantification, NIR spectroscopy is essential in various other fields, e.g. NIR imaging techniques in biophotonics, medical applications or used for characterization of food products. Its contribution in basic science and physical chemistry should be noted as well, e.g. in exploration of the nature of molecular vibrations or intermolecular interactions. One of the current development trends involves the miniaturization and simplification of instrumentation, creating prospects for the spread of NIR spectrometers at a consumer level in the form of smartphone attachments—a breakthrough not yet accomplished by any other analytical technique. A growing diversity in the related methods and applications has led to a dispersion of these contributions among disparate scientific communities. The aim of this Special Issue was to bring together the communities that may perceive NIR spectroscopy from different perspectives. It resulted in 30 contributions presenting the latest advances in the methodologies essential in near-infrared spectroscopy in a variety of applications.
n/a --- pocket-sized spectrometer --- standard germination tests --- total hydroxycinnamic derivatives --- hyperspectral image --- quantitative analysis modeling --- tissue --- chemotherapy --- FTIR spectroscopy --- cheese --- biomeasurements --- chemometrics --- affine invariance --- rapid identification --- biodiagnosis --- bioanalytical applications --- fat --- NIRS --- pixel-wise --- paraffin-embedded --- late preterm --- maize kernel --- photonics --- hyperspectral image processing --- image processing --- colorectal cancer --- test set validation --- deep convolutional neural network --- near-infrared fluorescence --- classification --- variety discrimination --- near-infrared hyperspectral imaging --- ensemble learning --- light --- origin traceability --- Paris polyphylla var. yunnanensis --- Fourier transform mid-infrared spectroscopy --- dry matter --- Fourier transform infrared spectroscopy --- hyperspectral imaging --- FT-NIR spectroscopy --- proximal sensing --- perfusion measurements --- near-infrared spectroscopy --- stained --- carotenoids --- cellular imaging --- perturbation --- direct model transferability --- clinical classifications --- counterfeit and substandard pharmaceuticals --- hyperspectral imaging technology --- spectral imaging --- SVM --- nutritional parameters --- extra virgin olive oil --- ethanol --- osteopathy --- living cells --- object-wise --- water-mirror approach --- Chrysanthemum --- bootstrapping soft shrinkage --- FTIR --- PLS-R --- multivariate data analysis --- combination bands --- binary dragonfly algorithm --- geographical origin --- Vitis vinifera L. --- glucose --- detection --- di-(2-picolyl)amine --- non-destructive sensor --- splanchnic --- adulteration --- animal origin --- melamine --- artemether --- MicroNIR™ --- brain --- fluorescent probes --- Folin–Ciocalteu --- SCiO --- support vector machine --- anharmonic quantum mechanical calculations --- PLSR --- Zn(II) --- RMSEP --- overtones --- blackberries --- pasta/sauce blends --- FT-IR --- partial least squares calibration --- partial least squares (PLS) --- auxiliary diagnosis --- handheld near-infrared spectroscopy --- precision viticulture --- partial least squares --- seeds vitality --- freeze-damaged --- near infrared --- discriminant analysis --- corn seed --- quantum chemical calculation --- anharmonic calculation --- Trichosanthis Fructus --- moisture --- analytical spectroscopy --- Raman spectroscopy --- NIR spectroscopy --- calibration transfer --- imaging --- water --- lumefantrine --- BRAF V600E mutation --- wavelength selection --- bone cancer --- imaging visualization --- near infrared spectroscopy --- raisins --- chemometric techniques --- data fusion --- prepared slices --- Ewing sarcoma --- biomonitoring --- Rubus fructicosus --- VIS/NIR hyperspectral imaging --- combinations bands --- quantitative analysis model --- partial least square regression --- DFT calculations --- TreeBagger --- antimalarial tablets --- accelerated aging --- agriculture --- crude drugs --- spectroscopy --- rice seeds --- PLS --- isotopic substitution --- multivariate calibration --- phytoextraction --- Fourier-transform near-infrared spectroscopy --- phenolics --- deparaffinized --- near-infrared (NIR) spectroscopy --- SIMCA --- counter propagation artificial neural network --- fructose --- PLS-DA --- ultra-high performance liquid chromatography --- aquaphotomics --- support vector machine-discriminant analysis --- hier-SVM --- DNA --- NIR --- support vector machine model --- API --- principal component analysis --- Folin-Ciocalteu
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