Design and Assessment of an Urban Circular Combined Truck–Drone Delivery System Using Continuum Approximation Models and Integer Programming

Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).The analysis of tandem truck–drone delivery systems has recently attracted the attention of the research community, mainly focused on extending classical operational research problems such as the multiple traveling salesperson or the vehicle-routing problem. In this paper, we explore the design of an urban massive combined delivery system using a continuum approximation (CA) method for a circular city characterized by a certain density of customers. Starting from a set of parameters defining the main characteristics of trucks and drones, a sectorization of the delivery area is first determined. Then, for a given truck capacity, the optimal number of trucks is obtained considering different scenarios using three integer programming models. We propose several performance indicators to compare the tandem approach with the alternative solely truck delivery system

An evolutionary algorithm for the design of hybrid fiber optic-coaxial cable networks in small urban areas

Telecommunication is one of the fastest growing business sectors. Future networks will need to integrate a wide variety of services demanding different qualities and capacities from the network. In this paper, network architecture based on hybrid fiber optic-coaxial cable (HFC) is proposed to develop cable integrated telematic services. An evolutionary algorithm is presented to solve the problem in suitable computation times when dealing with real times civil works problems. Finally we present the results over both problem library and real life scenarios

Designing rotating schedules by using Gröbner bases

In the current paper, we deal with the problem of designing rotating schedules from an algebraic computational approach. Specifically, we determine a set of Boolean polynomials whose zeros can be uniquely identified with the set of rotating schedules related to a given workload matrix and with the different constraints which are usually imposed to them.These polynomials constitute zero-dimensional radical ideals, whose reduced Gröbner bases can be computed to determine explicitly the set of rotating schedules which satisfy each constraint and hence, making possible to analyze their influence in the final pattern. Finally, we use this polynomial method to classify and characterize the set of rotating schedules related to a given number of shifts and work teams

Experimental techniques and numerical models to detect pollutant emission in the transport sector

25th International Conference on Urban Transport and the Environment, Urban Transport 2019; Aveiro; Portugal; 25 June 2019 through 27 June 2019; Code 155807In recent years, the growth of fossil fuel use and greenhouse gases emissions (GHGs) has been promoted by the population increase and development of the industry sector. Due to the increasing attention towards the effects of climate changes on quality of life, recent researches on pollutant formation processes have been developed in different sectors, especially in transportation. The last emission standards on pollutants impose limits on the dimensions and on the particle number of the particulate matter emissions, because of the highly dangerous effect on human health. To fight high concentrations of particulate matter (PM) emissions, a wide number of studies are addressed towards the definition of the most important parameters in effective production of particulate matter, especially in spark ignition engines. Physical processes such as mixture formation, engine operating parameters and fuel chemical properties strongly affect the soot formation in gasoline engines. The heat transfer process between the piston hot surface and the fuel gasoline during the post-injection phase is a key aspect of soot emissions for an engine. This paper is devoted to analyzing the fundamental parameters that are responsible for pollutant formation in the transport sector and the actual experimental and numerical techniques used to predict the environmental impact of engines

A short-turning policy for the management of demand disruptions in rapid transit systems

Rapid transit systems timetables are commonly designed to accommodate passenger demand in sections with the highest passenger load. However, disruptions frequently arise due to an increase in the demand, infrastructure incidences or as a consequence of fleet size reductions. All these circumstances give rise to unsupplied demand at certain stations, which generates passenger overloads in the available vehicles. The design of strategies that guarantee reasonable user waiting time with small increases of operation costs is now an important research topic. This paper proposes a tactical approach to determine optimal policies for dealing with such situations. Concretely, a short-turning strategy is analysed, where some vehicles perform short cycles in order to increase the frequency among certain stations of the lines and to equilibrate the train occupancy level. Turn-back points should be located and service offset should be determined with the objective of diminishing the passenger waiting time while preserving certain level of quality of service. Computational results and analysis for a real case study are provided.Junta de Andalucía P09-TEP-5022Natural Sciences and Engineering Research Council of Canada (NSERC) 39682-1

Counting and enumerating feasible rotating schedules by means of Gröbner bases

This paper deals with the problem of designing and analyzing rotating schedules with an algebraic computational approach. Specifically, we determine a set of Boolean polynomials whose zeros can be uniquely identified with the set of rotating schedules related to a given workload matrix subject to standard constraints. These polynomials constitute zero-dimensional radical ideals, whose reduced Gröbner bases can be computed to count and even enumerate the set of rotating schedules that satisfy the desired set of constraints. Thereby, it enables to analyze the influence of each constraint in the same.Junta de Andalucía P09-TEP-502

Analyzing the theoretical capacity of railway networks with a radial-backbone topology

In this work we propose a mechanism to optimize the capacity of the main corridor within a railway network with a radial-backbone or X-tree structure. The radial-backbone (or Xtree) structure is composed of two types of lines: the primary lines that travel exclusively on the common backbone (main corridor) and radial lines which, starting from the common backbone, branch out to individual locations. We define possible line configurations as binary strings and propose operators on them for their analysis, yielding an effective algorithm for generating an optimal design and train frequencies. We test our algorithm on real data for the high speed line Madrid-Seville. A frequency plan consistent with the optimal capacity is then proposed in order to eliminate the number of transfers between lines as well as to minimize the network fleet size, determining the minimum number of vehicles needed to serve all travel demand at maximum occupancy.Ministerio de Economía y Competitividad MTM2012-37048Junta de Andalucía P09-TEP-5022Junta de Andalucía P10-FQM-5849Canadian Natural Sciences and Engineering Research Council 39682-1

Cell formation using sequence information and neural networks

Most neural network approaches to the cell formation problem have been based on Competitive Learning-based algorithms such as ART (Adaptive Resonance Theory), Fuzzy Min- Max or Self-Organizing Feature Maps. These approaches do not use information on the sequence of operations on part types. They only use as input the binary part-machine incidence matrix. There are other neural network approaches such as the Hopfield model and Harmony Theory that have also been used to form manufacturing cells but again without considering the sequence of operations. In this paper we propose a sequence-based neural network approach for cell formation. The objective function considered is the minimization of transportation costs (including both intracellular and intercellular movements). Soft constraints on the minimum and maximum on the number of machines per cell can be imposed. The problem is formulated mathematically and shown to be equivalent to a quadratic programming integer program that uses symmetric, sequence-based similarity coefficients between each pair of machines. To solve such a problem two energy-based neural network approaches (Hopfield model and Potts Mean Field Annealing) are proposed

A Tandem Drone-ground Vehicle for Accessing Isolated Locations for First Aid Emergency Response in Case of Disaster

The collapse of infrastructures is very often a complicating factor for the early emergency actuations after a disaster. A proper plan to better cover the needs of the affected people within the disaster area while maintaining life-saving relief operations is mandatory hence. In this paper, we use a drone for flying over a set of difficult-to-access locations for imaging issues to get information to build a risk assessment as the earliest stage of the emergency operations. While the drone provides the flexibility required to visit subsequently a sort of isolated locations, it needs a commando vehicle in ground for (i) monitoring the deployment of operations and (ii) being a recharging station where the drone gets fresh batteries. This work proposes a decision-making process to plan the mission, which is composed by the ground vehicle stopping points and the sequence of locations visited for each drone route. We propose a Genetic Algorithm (GA) which has proven to be helpful in finding good solutions in short computing times. We provide experimental analysis on the factors effecting the performance of the output solutions, around an illustrative test instance. Results show the applicability of these techniques for providing proper solutions to the studied problem