93 research outputs found

    The vehicle routing problem with release dates and flexible time windows

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    In the context of the increasing demands for home delivery of fresh food, this article addresses the terminal distribution problem in an urban environment, which is called the vehicle routing problem with flexible time windows and order release dates (VRPFTWRD). This study develops a mathematical model and presents a set of valid inequalities based on the problem characteristics. According to the model and the inequalities, a branch-and-cut algorithm (B&C) is proposed for solving the problem. To verify the effectiveness of B&C, a set of test problems of different sizes is generated. The results show that the VRPFTWRD problem with up to 55 nodes can be solved to be optimality within one hour. Furthermore, B&C is used to solve vehicle routing problem (VRP) variants, and the results demonstrate that B&C can effectively solve VRP variants within a reasonable time.</p

    A capacitated vehicle routing problem with order available time in e-commerce industry

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    <p>In this article, a variant of the well-known capacitated vehicle routing problem (CVRP) called the capacitated vehicle routing problem with order available time (CVRPOAT) is considered, which is observed in the operations of the current e-commerce industry. In this problem, the orders are not available for delivery at the beginning of the planning period. CVRPOAT takes all the assumptions of CVRP, except the order available time, which is determined by the precedent order picking and packing stage in the warehouse of the online grocer. The objective is to minimize the sum of vehicle completion times. An efficient tabu search algorithm is presented to tackle the problem. Moreover, a Lagrangian relaxation algorithm is developed to obtain the lower bounds of reasonably sized problems. Based on the test instances derived from benchmark data, the proposed tabu search algorithm is compared with a published related genetic algorithm, as well as the derived lower bounds. Also, the tabu search algorithm is compared with the current operation strategy of the online grocer. Computational results indicate that the gap between the lower bounds and the results of the tabu search algorithm is small and the tabu search algorithm is superior to the genetic algorithm. Moreover, the CVRPOAT formulation together with the tabu search algorithm performs much better than the current operation strategy of the online grocer.</p

    Estimation and Inference of FAVAR Models

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    <p>The factor-augmented vector autoregressive (FAVAR) model is now widely used in macroeconomics and finance. In this model, observable and unobservable factors jointly follow a vector autoregressive process, which further drives the comovement of a large number of observable variables. We study the identification restrictions for FAVAR models, and propose a likelihood-based two-step method to estimate the model. The estimation explicitly accounts for factors being partially observed. We then provide an inferential theory for the estimated factors, factor loadings, and the dynamic parameters in the VAR process. We show how and why the limiting distributions are different from the existing results. Supplementary materials for this article are available online.</p

    MOESM1 of Construction and characterization of a high-quality cDNA library of Cymbidium faberi suitable for yeast one- and two-hybrid assays

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    Additional file 1. The sequencing and blast results of the randomly selected eight colonies in library construction

    P concentration and P content in wild type and transgenic plants.

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    <p>(A) P concentration. (B) P content. Roots and shoots were digested using the H<sub>2</sub>SO<sub>4</sub>–H<sub>2</sub>O<sub>2</sub> method. The P concentration was determined as described by Murphy and Riley <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0043501#pone.0043501-Murphy1" target="_blank">[30]</a>. Values are means ± SD (<i>n</i> = 5). * indicates statistically significant differences between transgenic lines and the wild type line under the same conditions at the 0.05 level, using Student's <i>t</i>-test. DW, dry weight. WT, wild type; L1, L2 and L3, transgenic lines; SP, sufficient phosphate (nutrient solution containing 1,000 µM KH<sub>2</sub>PO<sub>4</sub>); LP, low phosphate (nutrient solution containing 5 µM KH<sub>2</sub>PO<sub>4</sub>).</p

    P concentration in wild type and transgenic maize plants.

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    <p>On the 20th, 40th, 60th and 80th day of growth in the flowerpots, roots and shoots from wild type and transgenic plants were digested using the H<sub>2</sub>SO<sub>4</sub>–H<sub>2</sub>O<sub>2</sub> method in order to determine their P concentration. The P concentration was determined as described by Murphy and Riley <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0043501#pone.0043501-Murphy1" target="_blank">[30]</a>. (A) shoot P concentration. (B) root P concentration. (C) plant P concentration. Values are means ± SD (<i>n</i> = 5). P, phosphorus; WT, wild type; L1, L2 and L3, transgenic lines; SP, sufficient phosphate and LP, low phosphate.</p

    Wild type and transgenic maize yields from plants grown in flowerpots.

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    <p>Maize seeds were sown in flowerpots containing a naturally low-Pi soil (10 mg Pi kg<sup>−1</sup> soil) with either no additional KH<sub>2</sub>PO<sub>4</sub> (low phosphate, LP) or mixed with 600 mg KH<sub>2</sub>PO<sub>4</sub> (sufficient phosphate, SP) per kilogram soil. At harvest time, the ear length, number of grain rows and grain number per row of mature ears were recorded. Mature ears were dried and weighed to determine the grain yield per plant. Values are means ± SD (<i>n</i> = 5).</p>*<p>indicates statistically significant differences between transgenic lines and the wild type line under the same conditions at the 0.05 level, using Student's <i>t</i>-test. WT, wild type; L1, L2 and L3, transgenic lines; SP, sufficient phosphate and LP, low phosphate..</p

    Biomass and root/shoot ratio in wild type and transgenic plants.

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    <p>(A) biomass. (B) root/shoot ratio. The dry weights of roots and shoots were determined after they were dried to constant weight in an oven at 80°C. Values are means ± SD (<i>n</i> = 5). * indicates statistically significant differences between the transgenic lines and the wild type line under the same conditions at the 0.05 level, using Student's <i>t</i>-test. DW, dry weight; WT, wild type; L1, L2 and L3, transgenic lines; SP, sufficient phosphate (nutrient solution containing 1,000 µM KH<sub>2</sub>PO<sub>4</sub>); LP, low phosphate (nutrient solution containing 5 µM KH<sub>2</sub>PO<sub>4</sub>).</p
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