Angel A. Juan's research while affiliated with Universitat Politècnica de València and other places

Publications (32)

Article
Looking for an accurate and cost-effective solution to measure feed inventories, forecast the feed demand and allow feed suppliers to optimize inventories, production batches, and delivery routes.
Article
Society is facing a series of challenges, as the growth in urban population, the expansion of e-commerce, the pandemic moment (COVID-19), and many others leading to changes in companies’ supply chain, like reducing product delivery time and attention to consumer welfare, the environmental impact, to mention a few. The efficient management of logist...
Chapter
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Chest radiography is one of the most widely used imaging techniques for the detection and diagnosis of lung diseases. However, the correct extraction of information in these images is a tedious and challenging task that depends on the experience of radiologists. Due to this, in recent years, computer-aided diagnostic tools have been implemented to...
Chapter
Fog and Edge computing are opening up new opportunities to implement novel features of mobility, edge intelligence and end-user support. The successful implementation and deployment of Fog layers, as part of Cloud-to-thing-computing, largely depends on optimized allocation of tasks and applications to Fog and Edge nodes. Similarly as in other large...
Article
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The fast development in IoT and Cloud technologies has propelled the emergence of a variety of computing paradigms, among which Fog and Edge computing are salient computing technologies. Such new paradigms are opening up new opportunities to implement novel application scenarios, not possible before, by supporting features of mobility, edge intelli...
Article
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Feature selection (FS) was regarded as a global combinatorial optimization problem. FS is used to simplify and enhance the quality of high-dimensional datasets by selecting prominent features and removing irrelevant and redundant data to provide good classification results. FS aims to reduce the dimensionality and improve the classification accurac...
Article
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The techniques of halftoning are widely used in marketing because they reduce the cost of impression and maintain the quality of graphics. Halftoning converts a digital image into a binary image conformed by dots. The output of the halftoning contains less visual information; a possible benefit of this task is the reduction of ink when graphics are...
Article
Many real-life systems in production and transportation logistics are complex, large-scale, and stochastic in nature. As a consequence, simheuristic approaches – which integrate simulation inside a metaheuristic framework – are becoming increasingly popular in the optimization and simulation communities. In a simheuristic algorithm, time-consuming...
Article
Advances in Internet technologies have made it possible to gather, store, and process large quantities of data, often in real time. When considering smart and sustainable cities, this big data generates useful information and insights to citizens, service providers, and policy makers. Transforming this data into knowledge allows for empowering citi...
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The concepts of unmanned aerial vehicles and self-driving vehicles are gaining relevance inside the smart city environment. This type of vehicles might use ultra-reliable telecommunication systems, Internet-based technologies, and navigation satellite services to decide about the routes they must follow to efficiently accomplish their mission and r...
Article
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The concept of logistics tender or request for quotation is gaining importance among the logistics and transportation firms. Many long-term and long-distance transportation services are offered now under this type of reverse auction, and firms in the sector have to provide competitive prices if they want to win tenders. This paper explores the appl...
Article
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In this paper we discuss the team orienteering problem (TOP) with dynamic inputs. In the static version of the TOP, a fixed reward is obtained after visiting each node. Hence, given a limited fleet of vehicles and a threshold time, the goal is to design the set of routes that maximize the total reward collected. While this static version can be eff...
Article
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Soft constraints are quite common in real-life applications. For example, in freight transportation, the fleet size can be enlarged by outsourcing part of the distribution service and some deliveries to customers can be postponed as well; in inventory management, it is possible to consider stock-outs generated by unexpected demands; and in manufact...
Article
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Globalization and advances in information and communication technologies have boosted the use of Horizontal Cooperation (HC) practices in many industry sectors. In the current international market, these 'alliances' become especially relevant for small and medium organizations, which are forced to compete with large-scale corporations. This paper a...
Article
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Freight transportation is becoming an increasingly critical activity for enterprises in a global world. Moreover, the distribution activities have a non-negligible impact on the environment, as well as on the citizens’ welfare. The classical vehicle routing problem (VRP) aims at designing routes that minimize the cost of serving customers using a g...
Article
Recent advances in the telecommunication industry offer great opportunities to citizens and organizations in a globally connected world, but they also arise a vast number of complex challenges that decision makers must face. Some of these challenges can be modeled as combinatorial optimization problems (COPs). Frequently, these COPs are large-size,...
Article
In this paper we propose a Variable Neighborhood Search approach for the Crew Pairing Problem. This problem consist in assigning a crew to each of the flights of a flight scheduling, in a predefined time horizon. The main objective of the problem is to minimize the number of cabin crews needed to cover all the flights subject to a set of constraint...
Article
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Modern heuristics or metaheuristics are optimization algorithms that have been increasingly used during the last decades to support complex decision-making in a number of fields, such as logistics and transportation, telecommunication networks, bioinformatics, finance, and the like. The continuous increase in computing power, together with advancem...
Article
This paper analyzes the fleet mixed vehicle-routing problem with backhauls, a rich and realistic variant of the popular vehicle-routing problem in which both delivery and pick-up customers are served from a central depot using a heterogeneous and configurable fleet of vehicles. After a literature review on the issue and a detailed description of th...
Article
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This article presents the main results obtained during the development of the research project [email protected], contextualized in secondary education. The main purpose of this research is to identify those factors which in the opinion of teachers are more relevant when it comes to mainstream Information Technologies and Communication Technologies...
Article
The location routing problem (LRP) involves the three key decision levels in supply chain design, that is, strategic, tactical, and operational levels. It deals with the simultaneous decisions of (a) locating facilities (e.g., depots or warehouses), (b) assigning customers to facilities, and (c) defining routes of vehicles departing from and finish...
Conference Paper
In the face of sharp urbanization around the world, metropolitan areas have started different initiatives and projects to make cities more efficient and sustainable. Hereby logistics and transportation activities have a major impact in the development of so called ‘Smart Cities’. By addressing complex decision making problems through simulation and...
Article
Full-text available
Smart cities represent rich and dynamic environments in which a multitude of smart mobile devices (SMDs) interact among them by sharing data. SMDs require from fast access to online services, but they offer limited computing capabilities and battery lifetime. SMDs make frequent use of computation offloading, delegating computing-intensive tasks to...
Article
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In this study, we propose a general agent-based distributed framework where each agent is implementing a different metaheuristic/local search combination. Moreover, an agent continuously adapts itself during the search process using a direct cooperation protocol based on reinforcement learning and pattern matching. Good patterns that make up improv...
Conference Paper
Full-text available
This paper describes a simheuristic to improve urban waste collection processes. Growing city-populations around the world lead to an increased importance of an effective organisation in basic municipal activities such as waste management. The Waste Collection Problem (WCP) can be formulated as a special instance of the well-known Vehicle Routing P...
Chapter
Full-text available
This paper describes a simheuristic to improve urban waste collection processes. Growing city-populations around the world lead to an increased importance of an effective organisation in basic municipal activities such as waste management. The Waste Collection Problem (WCP) can be formulated as a special instance of the well-known Vehicle Routing P...
Conference Paper
The Location Routing Problem (LRP) involves three key decision levels (strategic, tactical, and operational) in logistics systems. In this paper a simulation-based approach is proposed to deal with the LRP, under uncertainty conditions, in an integrated way. This method uses a random choice of the depot and a fast routing heuristic to determine the...
Article
Trade credit refers to providing goods and services on a deferred payment basis. Commercial credit management is a matter of great importance for most small and medium enterprises (SMEs), since it represents a significant portion of their assets. Commercial lending involves assuming some credit risk due to exposure to default. Thus, the management...

Citations

... Motaghedi-Larijani and Aminnayeri (2017) incorporate VRP into the cross-docking problem via time windows, and address uncertainty using a queuing theory model. For a more comprehensive, updated and tabular review of the VRPCD literature, the avid reader is referred to Cota et al. (2022). ...
... This layer is at the top of the IoT stack and comprises the application support platform sublayer and the application sublayer. The former is used to support information collaboration, sharing, and interoperability, whereas the latter denotes applications used by various industries, such as smart supply chain management, intelligent logistics, energy management, and smart transportation [223,227]. The global market for the IoT has witnessed exponential growth in recent years [7,94]. ...
... The process of selecting appropriate and applicable variable values for a specific task is known as optimization [1][2][3]. Optimization exists in almost every domain, including job shop scheduling [4], feature selection [5][6][7], image processing [8,9], face detection and recognition [10], predicting chemical activities [11], classification [12,13], network allocation [14], internet of vehicles [15], routing [16], and neural network [17]. Due to the nature of real-world problems, Optimization becomes very challenging and has many difficulties such as multiobjectivity [18], memetic optimization [19], large-scale optimization [20], fuzzy optimization [21], uncertainties [22] and parameter estimation [23]. ...
... Circle detection (Cuevas et al., 2012) Template matching Motion estimation Halftoning (Ortega-Sánchez et al., 2020) Contrast enhancement (Guha et al., 2021) Bayesian networks Segmentation Object recognition (Pechebovicz et al., 2020) Machine learning Pixel's classification (Guerrero et al., 2012) Object recognition/Classification (Rodríguez-Esparza et al., 2020) ...
... Regarding position-dependent versions of the TOP, Reyes-Rubiano et al. [23] proposed a biased-randomized learnheuristic for solving the TOP with position-dependent rewards. In their work, rewards associated with each node were given by unknown (black-box) functions, the values of which were estimated based on existing observations and using learning mechanisms. ...
... In Juan et al. [170], the dynamic conditions of smart city environments are jointly addressed in a TOP system. Therefore, dealing with them requires the solving methodology to be able to react to these changes in real-time. ...
... There is, however, quite little work published in the literature on cost prediction of forwarding contracts. The work in [14] developed AI based models to predict the long-term cost of the logistics service, and attempted to construct a risk-aware interval for the prices to be offered in the bid, aiming to boost competitiveness in the application for tenders, and in addition, historical data was used to develop statistical learning models for predicting the success likelihood of a tender based on the actual data and predicted service prices achieved from previous stage. In [5], a trapezoidal neutrosophic fuzzy analytical hierarchy process (TNF-AHP) was proposed to determine the most significant criteria that were used to predict transportation cost by an artificial neural network (ANN) model, which, claimed by the authors, can be also used in supply chain management and inventory control management. ...
... Efficient randomization has important research applications in a variety of other areas as well, such as in modeling and simulation (Greasley & Edwards, 2021;Rabe et al., 2020;Zhang et al., 2019), domain randomization (Tobin et al., 2017) for sim-to-real transfer learning (Zhao et al., 2020), among others. ...
... The emergence of demand-based economics (services) and e-commerce (products) has exponentially increased the number of T&M operations in urban and metropolitan areas. Thus, T&M activities have a profound effect on the development of so-called smart cities, the scope of which combines sustainable development with intelligent management of real-time data collected through IoT devices (e.g., sensors, cameras, etc.) and analyzed through cloud systems to improve the performance of various services in urban areas [1]. In recent years, city governments have implemented various action plans in order to make cities more energy efficient and environmentally sustainable. ...
... If this objective function does not correctly represent the variables to be optimized in a system, the effort involved in the optimization model is almost useless. Following the seminal work of Fikar et al. [10], this paper describes a hybrid approach which combines concepts from discrete-event simulation (DES) [11] with heuristic algorithms [12] and biased-randomized techniques [13]. As we will discuss in this paper, the 'discrete-event heuristic' (DEH) approach allows us to efficiently deal with time dependencies and synchronization issues in dynamic optimization problems. ...