A branch and cut algorithm for the VRP with satellite facilities

An important aspect of the vehicle routing problem (VRP) that has been largely overlooked is the use of satellite facilities to replenish vehicles during a route. When possible, satellite replenishment allows the drivers to continue making deliveries until the close of their shift without necessarily returning to the central depot. This situation arises primarily in the distribution of fuels and certain retail items. When demand is random, optimizing customer routes a priori may result in significant additional costs for a particular realization of demand. Satellite facilities are one way of safeguarding against unexpected demand. This paper presents a branch and cut methodology for solving the VRP with satellite facilities subject to capacity and route time constraints. We begin with a mixed-integer linear programming formulation and then describe a series of valid inequalities that can be used to cut off solutions to the linear programming relaxation. Several separation heuristics are then outlined that are used to generate the cuts. Embedded in the methodology is a VRP heuristic for finding good feasible solutions at each stage of the computations. Results are presented for a set of problems derived from our experience with a leading propane distributor.     

Straining phenomena of POY revealed by thermal retraction and other techniques

Partially oriented polyesters yarns (POY) were strained at different strain rates (0.03–12.00 min^?1) and temperatures above and below T_g (3–92°C). Thermal retraction, density, DSC, and WAXS techniques show that strain-induced crystallization takes place by straining at temperatures above as well as below T_g. Above T_g, depending upon the strain rate, two regimes are observed: Below the strain rate of 1.5 min^?1, the flow regime; the degree of crystallinity is reduced as the strain rate increases. Above the strain rate of 1.5 min^?1, the strain-induced crystallization regime; the degree of crystallinity increases as the strain rate increases. Thermal retraction, stress–relaxation, and sonic modulus techniques indicate that, upon cold straining, instead of the original T_g at 65–69°C, two glass transitions occur: an upper T_g (u) and a lower T_g (l). For POY strained at 3°C and at a strain rate of 10 min^?1, the values are 78°C and 37°C, respectively. The higher the strain rate and the lower the straining temperature, the large the difference between T_g (u) and T_g (l).     

Multimodal bioimaging based on gold nanorod and carbon dot nanohybrids as a novel tool for atherosclerosis detection

Advanced biocompatible and robust platforms equipped with diverse properties are highly required in biomedical imaging applications for the early detection of atherosclerotic vascular disease and cancers. Designing nanohybrids composed of noble metals and fluorescent materials is a new way to perform multimodal imaging to overcome the limitations of single-modality counterparts. Herein, we propose the novel design of a multimodal contrast agent; namely, an enhanced nanohybrid comprising gold nanorods (GNRs) and carbon dots (CDs) with silica (SiO₂) as a bridge. The nanohybrid (GNR@SiO₂@CD) construction is based on covalent bonding between SiO₂ and the silane-functionalized CDs, which links the GNRs with the CDs to form typical core–shell units. The novel structure not only retains and even highly improves the optical properties of the GNRs and CDs, but also possesses superior imaging performance in both diffusion reflection (DR) and fluorescence lifetime imaging microscopy (FLIM) measurements compared with bare GNRs or fluorescence dyes and CDs. The superior bioimaging properties of the GNR@SiO₂@CD nanohybrids were successfully exploited for in vitro DR and FLIM measurements of macrophages within tissue-like phantoms, paving the way toward a theranostic contrast agent for atherosclerosis and cancer.

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Experimental investigation of the influence of the relative position of the scattering layer on image quality: the shower curtain effect

The imaging quality of optical systems in a turbid environment is influenced not only by the content of the turbid layer between the object and the optical receiver but also by the inhomogeneity of that medium. This is important, particularly when imaging is performed through clouds, nonhomogeneous layers of dust, or over vertical or slant paths through the atmosphere. Forward small-angle scattering influences image quality and blur more severely when the scattering layer is closer to the receiver. In this study it is the influence of the relative position of the scattering layer on the image quality and modulation transfer function (MTF) that is investigated. The scattering layer in controlled laboratory experiments consists of calibrated polystyrene particles of known size and quantity in a small cuvette. A point source was imaged by a computerized imaging system through a layer containing polystyrene particles, and the point-spread function (PSF) was recorded. The aerosol MTF was calculated using the measured PSF. The MTF was measured as a function of changing relative distance of the scattering layer from the receiver, whereas the object-plane-to-receiver distance was constant. The experimental results were compared to theoretical shower curtain effect models based on the solution from radiative transfer theory under the small-angle approximation. Although the general trend of the experimental results certainly agrees with the theoretical models, it could be that the small-angle approximation method might be of limited validity at such low spatial frequencies. Aggregation also causes some disagreement with predictions from theory.     

Common coupling and pointer variables,with application to a Linux case study

Both common coupling and pointer variables can exert a deleterious effect on the quality of software. The situation is exacerbated when global variables are assigned to pointer variables, that is, when an alias to a global variable is created. When this occurs, the number of global variables increases, and it becomes considerably harder to compute quality metrics correctly. However, unless aliasing is taken into account, variables may incorrectly appear to be unreferenced (neither defined nor used), or to be used without being defined. These ideas are illustrated by means of a case study of common coupling in the Linux kernel.

Combinatorial Optimization and Performance Analysis of a Multi-arm Cartesian Robotic Fruit Harvester—Extensions of Graph Coloring

A mobile melon robotic harvester consisting of multiple Cartesian manipulators, each with three degrees of freedom, is being developed. In order to design an optimal robot in terms of number of arms, manipulator capabilities, and robot speed, a method of allocating the fruits to be picked by each manipulator in a way that yields the maximum harvest has been developed. Such a method has already been devised for a multi-arm robot with 2DOF each. The maximum robotic harvesting problem was shown there to be an example of the maximum k-colorable subgraph problem (MKCSP) on an interval graph. However, for manipulators with 3DOF, the additional longitudinal motion results in variable intervals. To overcome this issue, we devise a new model based on the color-dependent interval graph (CDIG). This enables the harvest by multiple robotic arms to be modeled as a modified version of the MKCSP. Based on previous research, we develop a greedy algorithm that solves the problem in polynomial time, and prove its optimality using induction. As with the multi-arm 2DOF robot, when simulated numerous times on a field of randomly distributed fruits, the algorithm yields a nearly identical percentage of fruit harvested for given robot parameters. The results of the probabilistic analysis developed for the 2DOF robot was modified to yield a formula for the expected harvest ratio of the 3DOF robot. The significance of this method is that it enables selecting the most efficient actuators, number of manipulators, and robot forward velocity for maximal robotic fruit harvest.     

Automatic negotiation: playing the domain instead of the opponent

An automated negotiator is an intelligent agent whose task is to reach the best possible agreement. We explore a novel approach to developing a negotiation strategy, a ‘domain-based approach’. Specifically, we use two domain parameters, reservation value and discount factor, to cluster the domain into different regions, in each of which we employ a heuristic strategy based on the notions of temporal flexibility and bargaining strength. Following the presentation of our cognitive and formal models, we show in an extensive experimental study that an agent based on that approach wins against the top agents of the automated negotiation competition of 2012 and 2013, and attained the second place in 2014.     

Gradient interpenetrating polymer networks. I. Poly(ether urethane) and polyacrylamide IPN

The swelling properties of poly(ether urethane)s and the preparation of interpenetrating polymer networks (IPNs) from a poly(ether urethane) thermoplastic elastomer and hydrogel forming polyacrylamide have been studied. The acrylamide monomer was polymerized with simultaneous crosslink formation, in the presence of the swollen thermoplastic elastomer. Upon removal of the swelling solvent, an IPN was obtained which absorbed water in the manner of a hydrogel but had mechanical properties superior to a hydrogel.     

STYLISTIC FEATURE SETS AS CLASSIFIERS OF DOCUMENTS ACCORDING TO THEIR HISTORICAL PERIOD AND ETHNIC ORIGIN

This research investigates classification of documents according to the ethnic group of their authors and/or to the historical period when the documents were written. The classification is done using various combinations of six sets of stylistic features: quantitative, orthographic, topographic, lexical, function, and vocabulary richness. The application domain is Jewish Law articles written in Hebrew-Aramaic, languages that are rich in their morphological forms. Four popular machine learning methods have been applied. The logistic regression method led to the best accuracy results: about 99.6% while classifying to the ethnic group of their authors or to the historical period when the articles were written and about 98.3% while classifying to both classifications. The quantitative feature set was found as very successful and superior to all other sets. The lexical and function feature sets have also been found to be useful. The quantitative and the function features are domain independent and language independent. These two feature sets might be generalized to similar classification tasks for other languages and can therefore be useful for the text classification community at large.