A genetic algorithm for vehicle routing in logistic networks with practical constraints

We optimise a postal delivery problem with time and capacity constraints imposed on vehicles and nodes of the logistic network. Time constraints relate to the duration of routes, whereas capacity constraints concern technical characteristics of vehicles and postal operation outlets. We consider a method which can be applied to a brownfield scenario, in which capacities of outlets can be relaxed and prospective hubs identified. As a solution, we apply a genetic algorithm and test its properties both in small case studies and in a simulated problem instance of a larger (i.e. comparable with real-world instances) size. We show that the genetic operators we employ are capable of switching between solutions based on direct origin-to-destination routes and solutions based on transfer connections, depending on what is more beneficial in a given problem instance. Moreover, the algorithm correctly identifies cases in which volumes should be shipped directly, and those in which it is optimal to use transfer connections within a single problem instance, if an instance in question requires such a selection for optimality. The algorithm is thus suitable for determining hubs and satellite locations. All considerations presented in this paper are motivated by real-life problem instances experienced by the Polish Post, the largest postal service provider in Poland, in its daily plans of delivering postal packages, letters and pallets.

A Concurrent Testing Facility Approach to Validate Small Satellite Combined Operations

Federated remote laboratories allow for the execution of experiments ex situ. The coordination of several laboratories can be used to perform concurrent experiments of combined space operations. However, the latency of the communications between facilities is critical to performing adequate real-time experiments. This paper presents an approach for conducting coordinated experiments between floating platforms at two remote laboratories. Two independently designed platforms, one at Luleå University of Technology and the other at La Sapienza University of Rome, were established for this purpose. A synchronization method based on the Simple Network Time Protocol was created, allowing the offset and delay between the agents to be measured.Both platforms exchange data about their measured time and pose through a UDP/IP protocol over the internet. This approach was validated with the execution of simulated operations. A first demonstrative experiment was also performed showing the possibility to realize leader/follower coordinated operations. The results of the simulations and experiments showed communication delays on the order of tens of milliseconds with no significant impact on the control performance. Consequently, the suggested protocol was proven to be adequate for conducting coordinated experiments in real time between remote laboratories.

Influence of Level of Detail (LOD) in Hydraulic Model Geometry with Demand Allocation by Voronoi Polygon Method on Chosen Parameters

Deciding on the level of model complexity is one of the first decisions that has to be made before engaging in the creation of a functional hydraulic model of a municipal water supply system. There are a number of influencing factors such as time needed to simulate the network, time needed to create such model and ease of use. The aim of this work is to prove that level of detail has influence on parameters such as pressure at measurement points, spread of flow speed and flow volume at different parts of mains. The Voronoi polygon method is one of the basic demand allocation methods, which, in the event of a different number of junctions depending on model complexity, has to generate a varying number of polygons of different sizes used to aggregate the demands.

Research on fine tuning parameter insulator identification based on YOLOV4 algorithm

Aiming at the problem that the training network time of YOLOV4 algorithm is too long due to the large data set of aerial insulator images, a method based on YOLOV4 algorithm is proposed to shorten the training time by fine-tuning parameters without affecting the positioning detection accuracy. Based on the development of UBANTU virtual machine, through CUDA and CUDNN environment configuration, and through the detection and verification of insulator aerial photo data set, the feasibility of accurate positioning of insulators under the condition of fine tuning parameters of YOLOV4 algorithm is successfully proved.

First measurement service applied to event dating for reliable business transactions: metrology for digital transformation using Colombian legal time.

Diffusing the legal time in Colombia is one missional assessment of INM (National Metrology Institute of Colombia). This is done via a public IP through an NTP server (Network Time Protocol Server) disciplined to the National Standard of Time and Frequency. So, the companies can synchronize their servers, but they do not have certainty about the difference that exists between the time of the client-server and the legal time of the INM server because there is not a constant verification implemented by themselves. In Colombia, the demand for the legal time service has increased because it is used by many companies due to the rise of innovative applications such as time-stamp, digital signature, electronic invoice, and economic transactions. This has an impact on the economic environment of a country for world trade. For this reason, the INM of Colombia implemented a new service to measure the synchronization offset with the legal time, which allows the companies to have a new service that generates reliability respecting the time they use to provide their services. Inspired by the INM contribution to the international comparison Universal Time Coordinated (UTC) and the intercomparison of the National Standards of Time and Frequency implemented through the SIM time scale (SIMT) using GPS (Global Positioning System), the INM developed a customized application for national comparison using NTP. As a result, this is the first remote measurement service as evidence of metrology for digital transformation in Colombia in the field of time and frequency.

JMASM 55: MATLAB Algorithms and Source Codes of 'cbnet' Function for Univariate Time Series Modeling with Neural Networks (MATLAB)

Artificial Neural Networks (ANN) can be designed as a nonparametric tool for time series modeling. MATLAB serves as a powerful environment for ANN modeling. Although Neural Network Time Series Tool (ntstool) is useful for modeling time series, more detailed functions could be more useful in order to get more detailed and comprehensive analysis results. For these purposes, cbnet function with properties such as input lag generator, step-ahead forecaster, trial-error based network selection strategy, alternative network selection with various performance measure and global repetition feature to obtain more alternative network has been developed, and MATLAB algorithms and source codes has been introduced. A detailed comparison with the ntstool is carried out, showing that the cbnet function covers the shortcomings of ntstool.