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Titlebook: Learning and Intelligent Optimization; 14th International C Ilias S. Kotsireas,Panos M. Pardalos Conference proceedings 2020 Springer Natur

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A Matheuristic Algorithm for Solving the Vehicle Routing Problem with Cross-Docking,le products from a set of suppliers to a set of customers through a cross-dock facility, such that the operational and transportation costs are minimized, without violating the vehicle capacity and time horizon constraints. A two-phase matheuristic approach that uses the routes of the local optima o
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Physical Activity as a Risk Factor in the Progression of Osteoarthritis: A Machine Learning Perspecpensive commonly measuring changes in joint morphology and function. So, it is very important to diagnose KOA early, which can be achieved with early identification of significant risk factors in clinical data. Our objective in this paper is to investigate the predictive capacity of physical activit
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Early Detection of Eating Disorders Through Machine Learning Techniques,tion of the high prevalence of excess weight and the early appearance of metabolic pathologies, but also due to the significant presence of Eating Disorders (EDs). EDs, in fact, continue to be underdiagnosed by pediatric professionals and many adolescents go untreated, do not recover or reach only p
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A Class of Linear Programs Solvable by Coordinate-Wise Minimization,d) convex problems it may not find global minima. We present a class of linear programs that coordinate-wise minimization solves exactly. We show that dual LP relaxations of several well-known combinatorial optimization problems are in this class and the method finds a global minimum with sufficient
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Travel Times Equilibration Procedure for Route-Flow Traffic Assignment Problem,equilibrium route-flow assignment can be easily obtained by implementing equilibration procedure together with simple rules for sequential extension and/or by reducing the set of active routes. Accurate route-flow solution for the small Sioux Falls network is found via the developed algorithm and de
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Randomized Algorithms for Some Sequence Clustering Problems,acluster sum of squared distances from cluster elements to its centroid. In the second problem, we need to partition a sequence into two clusters minimizing cardinality-weighted intracluster sums of squared distances from clusters elements to their centers; the center of the first cluster is its cen
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