A polyhedral approach for the generalized assignment problem.

The generalized assignment problem (GAP) consists of finding a maximal profit assignment of n jobs over m capacity constrained agents, whereby each job has to be processed by only one agent. This contribution approaches the GAP from the polyhedral point of view. A good upper bound is obtained by approximating the convex hull of the knapsack constraints in the GAP-polytope using theoretical work of Balas. Based on this result, we propose a procedure for finding close-to-optimal solutions, which gives us a lower bound. Computational results on a set of 60representative and highly capacitated problems indicate that these solutions lie within 0.06% of the optimum. After applying some preprocessing techniques and using the obtained bounds, we solve the generated instances to optimality by branch and bound within reasonable computing time.Assignment;

A polyhedral approach for the generalized assignment problem

The generalized assignment problem (GAP) consists of finding a maximal profit assignment of n jobs over m capacity constrained agents, whereby each job has to be processed by only one agent. This contribution approaches the GAP from the polyhedral point of view. A good upper bound is obtained by approximating the convex hull of the knapsack constraints in the GAP-polytope using theoretical work of Balas. Based on this result, we propose a procedure for finding close-to-optimal solutions, which gives us a lower bound. Computational results on a set of 60representative and highly capacitated problems indicate that these solutions lie within 0.06% of the optimum. After applying some preprocessing techniques and using the obtained bounds, we solve the generated instances to optimality by branch and bound within reasonable computing time.status: publishe

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Identification of (antioxidative) plants in herbal pharmaceutical preparations and dietary supplements.

&lt;p&gt;The standard procedures for the identification, authentication, and quality control of medicinal plants and herbs are nowadays limited to pure herbal products. No guidelines or procedures, describing the detection or identification of a targeted plant or herb in pharmaceutical preparations or dietary supplements, can be found. In these products the targeted plant is often present together with other components of herbal or synthetic origin. This chapter describes a strategy for the fast development of a chromatographic fingerprint approach that allows the identification of a targeted plant in herbal preparations and dietary supplements. The strategy consists of a standard chromatographic gradient that is tested for the targeted plant with different extraction solvents and different mobile phases. From the results obtained, the optimal fingerprint is selected. Subsequently the samples are analyzed according to the selected methodological parameters, and the obtained fingerprints can be compared with the one obtained for the pure herbal product or a standard preparation. Calculation of the dissimilarity between these fingerprints will result in a probability of presence of the targeted plant. Optionally mass spectrometry can be used to improve specificity, to confirm identification, or to identify molecules with a potential medicinal or antioxidant activity.&lt;/p&gt;</p

Spectroscopic Fingerprint Of Tea Varieties By Surface Enhanced Raman Spectroscopy

The fingerprinting method is generally performed to determine specific molecules or the behavior of specific molecular bonds in the desired sample content. A novel, robust and simple method based on surface enhanced Raman spectroscopy (SERS) was developed to obtain the full spectrum of tea varieties for detection of the purity of the samples based on the type of processing and cultivation. For this purpose, the fingerprint of seven different varieties of tea samples (herbal tea (rose hip, chamomile, linden, green and sage tea), black tea and earl grey tea) combined with silver colloids was obtained by SERS in the range of 200-2000 cm(-1) with an analysis time of 20 s. Each of the thirty-nine tea samples tested showed its own specific SERS spectra. Principal Component Analysis (PCA) was also applied to separate of each tea variety and different models developed for tea samples including three different models for the herbal teas and two different models for black and earl grey tea samples. Herbal tea samples were separated using mean centering, smoothing and median centering pre-processing steps while baselining and derivatisation pre-processing steps were applied to SERS data of black and earl grey tea. The novel spectroscopic fingerprinting technique combined with PCA is an accurate, rapid and simple methodology for the assessment of tea types based on the type of processing and cultivation differences. This method is proposed as an alternative tool in order to determine the characteristics of tea varieties.Wo