The Eco-Friendly Intermodal Delivery Network

The design of the distribution process is a strategic issue for almost every company. As the use of advanced technology and automation increases in manufacturing and logistics, the implementation of autonomous and electrical transportation, such as driverless vehicles and electric trucks, has become an interesting topic of study within the last few years, with the main objective of minimizing distribution costs and delivery times. The purpose of this research is to prove that intermodal delivery networks, which may combine a train and several electric vehicles, are more efficient and environmentally friendly than unimodal networks for high volume and long haul transportation, regardless of the customers’ distribution. This is only applicable if demand does not fall within the capacity restriction of road transportation vehicles. To do so, this paper utilizes an optimization algorithm that consists of a feedback mechanism between K-means and a genetic algorithm, which finds the optimal routes between distribution centers and surrounding customers as a multiple traveling salesman problem (mTSP)

Tuberculosis en ovino: epidemiología, patología y evaluación de técnicas diagnósticas

5 páginas, 2 tablas, 1 figura.--Trabajo presentado al: XL Congreso Nacional y el XVI Congreso Internacional de la Sociedad Española de Ovinotecnia y Caprinotecnia. (Castellón de la Plana, España, 16-18 septiembre 2015).Peer Reviewe

Optimization of a truck-drone in tandem delivery network using k-means and genetic algorithm

Purpose: The purpose of this paper is to investigate the effectiveness of implementing unmanned aerial delivery vehicles in delivery networks. We investigate the notion of the reduced overall delivery time, energy, and costs for a truck-drone network by comparing the in-tandem system with a stand-alone delivery effort. The objectives are (1) to investigate the time, energy, and costs associated to a truck-drone delivery network compared to standalone truck or drone, (2) to propose an optimization algorithm that determines the optimal number of launch sites and locations given delivery requirements, and drones per truck, (3) to develop mathematical formulations for closed form estimations for the optimal number of launch locations, optimal total time, as well as the associated cost for the system. Design/methodology/approach: The design of the algorithm herein computes the minimal time of delivery utilizing K-means clustering to find launch locations, as well as a genetic algorithm to solve the truck route as a traveling salesmen problem (TSP). The optimal solution is determined by finding the minimum cost associated to the parabolic convex cost function. The optimal min-cost is determined by finding the most efficient launch locations using K-means algorithms to determine launch locations and a genetic algorithm to determine truck route between those launch locations.  Findings: Results show improvements with in-tandem delivery efforts as opposed to standalone systems. Further, multiple drones per truck are more optimal and contribute to savings in both energy and time. For this, we sampled various initialization variables to derive closed form mathematical solutions for the problem. Originality/value: Ultimately, this provides the necessary analysis of an integrated truck-drone delivery system which could be implemented by a company in order to maximize deliveries while minimizing time and energy. Closed-form mathematical solutions can be used as close estimators for final costs and time

Sheep as a potential source of bovine TB: epidemiology, pathology and evaluation of diagnostic techniques

Bovine tuberculosis (TB) infection is infrequently diagnosed in sheep. Most reports are from single individual cases or flock outbreaks. However, in Spain several outbreaks have been reported recently, all of which had epidemiological links with TB‐infected cattle herds. A total of 897 sheep suspected of being infected with TB and belonging to 23 flocks cohabiting with TB‐infected cattle herds and/or goats were tested between 2009 and 2013 in Galicia (north‐western Spain), using pathological, immunological and molecular techniques. Of these, 50.44% were positive by culture, 83.23% by histopathology and 24.92%, 4.86% and 59.42% by single intradermal tuberculin test (SITT), interferon‐γ and ELISA, respectively. Results suggest that in circumstances akin to those in our study, sheep may be considered as a potential source of TB. We conclude that under similar conditions, serious consideration should be given to TB testing sheep, as they may represent a potential risk to other susceptible co‐habiting species. The SITT and ELISA are recommended as the simplest and most cost‐effective initial approaches for the diagnosis of TB in sheep under field conditions. However, when possible, interferon‐γ should be applied to increase sensitivity.This project was supported by INIA RTA2011‐00010‐00‐00 (FEDER co‐funded) and EU FP7 grant APHAEA (EMIDA ERA‐NET).Peer Reviewe