Andriy Mazayev

Solutions in Under 10 Seconds for Vehicle Routing Problems with Time Windows Using Commodity Computers

I3FR (Intelligent Fresh Food Fleet Router) is a project in development by the University of the Algarve and X4DEV, Business Solutions. One of the I3FR’s main goals is to build a system for the optimization of the distribution of fresh goods using a fleet of vehicles. The most similar problem in literature is the well established and experimented Vehicle Routing Problem with Time Windows, which is by nature a multiple objective problems where the number of vehicles and the total traveled distance must be minimized.

A Solution for a Real-time Stochastic Capacitated Vehicle Routing Problem with Time Windows

Real-time distribution planning presents major difficulties when applied to large problems. Commonly, this planning is associated to the capacitated vehicle routing problem with time windows (CVRPTW), deeply studied in the literature.In this paper we propose an optimization system developed to be integrated with an existing Enterprise Resource Planning (ERP) without causing major disruption to the current distribution process of a company. The proposed system includes: a route optimization module, a module implementing the communications within and to the outside of the system, a non-relational database to provide local storage of information relevant to the optimization procedure, and a cartographic subsystem. The proposed architecture is able to deal with dynamic problems included in the specification of the project, namely: arrival of new orders while already optimizing as well as locking and closing of routes by the system administrator. A back-office graphical interface was also implemented and some results are presented.

GACN: Self-Clustering Genetic Algorithm for Constrained Networks

Extending the lifespan of a wireless sensor network is a complex problem that involves several factors, ranging from device hardware capacity (batteries, processing capabilities, and radio efficiency) to the chosen software stack, which is often unaccounted for by the previous approaches. This letter proposes a genetic algorithm-based clustering optimization method for constrained networks that significantly improves the previous state-of-the-art results, while accounting for the specificities of the Internet engineering task force, Constrained RESTful Environment (CoRE), standards for data transmission and specifically relying on CoRE interfaces, which fit this purpose very well.

Heuristic approach for data gathering in wireless sensor networks

Future device to device communication using the LTE system bring new opportunities for application development. In the case of wireless sensor networks, unmanned aerial vehicles with LTE capabilities could be used to increase the network lifetime, while ensuring high transfer rates between LTE capable sensor nodes and the aerial vehicles. In this article we propose a hybrid heuristic algorithm able to design a set of efficient paths to gather the data generated by sensor nodes, which are scattered over a given area, while ensuring that data collected will not arrive outdated to the base station. This is particularly useful when sensors generate data with time delivery deadlines. Results show that the approach is able to solve the data gathering problem efficiently presenting, for most data sets and time delivery deadline ranges, a high certainty degree regarding the quality of the solution.

Integration of a Real-Time Stochastic Routing Optimization Software with an Enterprise Resource Planner

In order to manage their activities in a centralized manner, an Enterprise Resource Planning (ERP) software is a fundamental tool to many companies. As a generic software, many times it’s necessary to add new functionalities to the ERP in order to improve and to adapt/suite it to the companies’ processes. The Intelligent Fresh Food Fleet Router (i3FR) project aims to meet the needs expressed by several companies, namely the usefulness of a tool that makes “intelligent” management of the food distribution logistics. This “intelligence” presupposes interconnection capacity of various platforms (e.g., fleet management, GPS, and logistics), and active communication between them in order to optimize and enable integrated decisions.

An Energy-Aware Resource Design Model for Constrained Networks

The Internet of Things is expected to incorporate objects and sensor networks of all kinds, and in particular, constrained sensor networks where energy consumption is a critical issue. In order to increase the lifetime of such networks, intelligent and standard-based solutions should be used. Here, we address this challenge through the use of CoRE interfaces for the resource design. These interfaces allow the server side to compose/organize resources and the client side to discover and determine how to consume such resources, besides allowing decisions to be easily integrated into the operation of the network. An energy-aware resource design model is proposed, based on CoRE interfaces, for the design of resources matching client needs. Based on this model, we develop an algorithm that proved to be energy efficient.

Interoperability in IoT Through the Semantic Profiling of Objects

The emergence of smarter and broader people-oriented IoT applications and services requires interoperability at both data and knowledge levels. However, although some semantic IoT architectures have been proposed, achieving a high degree of interoperability requires dealing with a sea of non-integrated data, scattered across vertical silos. Also, these architectures do not fit into the machine-to-machine requirements, as data annotation has no knowledge on object interactions behind arriving data. This paper presents a vision of how to overcome these issues. More specifically, the semantic profiling of objects, through CoRE related standards, is envisaged as the key for data integration, allowing more powerful data annotation, validation, and reasoning. These are the key blocks for the development of intelligent applications.

Semantic web thing architecture

As the Internet of Things evolves and matures, the number of connected devices and the amount of generated data grows exponentially. Integrative standards and API design patterns are required to deal with this fast growth, while easing machine to machine communication and promoting ubiquitous computing. This paper discusses the W3C Web of Things model that is currently in the process of standardization, and presents our overview and implementation of this model.

Semantically Enriched Hypermedia APIs for Next Generation IoT

As the Internet of Things is gaining momentum, the number of Internet connected devices is growing exponentially, as well as the data generated by them. This raises several issues to solve in this field, most notably the ones regarding interoperability between various devices. To ease Machine-to-Machine communication, new data models must be created to explicitly describe devices and their capabilities in a standardized way. This paper discusses the IETF’s Media Types for Hypertext Sensor Markup data model that is currently in the design process. First, we present an overview of how semantic Web technologies can be used create self-describing APIs, and then present a smart home use case that relies on these technologies.

Resource Design in Constrained Networks for Network Lifetime Increase

As constrained “things” become increasingly integrated with the Internet and accessible for interactive communication, energy efficient ways to collect, aggregate, and share data over such constrained networks are needed. In this paper, we propose the use of constrained RESTful environments interfaces to build resource collections having a network lifetime increase in mind. More specifically, based on existing atomic resources, collections are created/designed to become available as new resources, which can be observed. Such resource design should not only match client’s interests, but also increase network lifetime as much as possible. For this to happen, energy consumption should be balanced/fair among nodes so that node depletion is delayed. When compared with previous approaches, results show that energy efficiency and network lifetime can be increased while reducing control/registration messages, which are used to set up or change observations.