Browsing by Keyword "Harmony search"
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Item A bi-objective harmony search approach for deploying cost-effective multi-hop communications over large-area wildfires(Springer Verlag, 2014) Bilbao, Miren Nekane; Del Ser, Javier; Salcedo-Sanz, Sancho; Gil-López, Sergio; Portilla-Figueras, José Antonio; Klett, Fanny; Abraham, Ajith; Herrero, Álvaro; Baruque, Bruno; de Carvalho, André C.P.L.F.; Quintián, Héctor; Corchado, Emilio; Quintián, Héctor; de la Puerta, José Gaviria; Ferreira, Iván García; Bringas, Pablo García; IAGlobal phenomena such as the climate warming and the consequently growing scales of wildfires motivate the need for computationally efficient tools and frameworks for assisting brigade commanders in their coordination and management duties. However, the current worldwide economical situation usually imposes severe budgetary constraints that ultimately impact on the inventory of available firefighting resources and support equipment. In this context this manuscript presents a novel meta-heuristically empowered scheme which determines the position and model of a number of wireless communication relays to be deployed over a large-scale wildfire area under a Pareto-optimal strategy: to balance between coverage and cost of the deployment. The system model also allows for multi-hop links among the brigades operating on the area. Specifically, Harmony Search heuristics are utilized to iteratively refine the position and models of the relays. Simulation results over synthetic scenarios are discussed, from which future research lines stem towards formulations of increased realism including the allocation of radio channels and orography-aware coverage areas.Item A comparative study of two hybrid grouping evolutionary techniques for the capacitated P-median problem(2012-09) Landa-Torres, I.; Del Ser, J.; Salcedo-Sanz, S.; Gil-Lopez, S.; Portilla-Figueras, J. A.; Alonso-Garrido, O.; Tecnalia Research & Innovation; IAThis paper addresses the application of two different grouping-based algorithms to the so-called capacitated P-median problem (CPMP). The CPMP is an NP-complete problem, well-known in the operations research field, arising from a wide spectrum of applications in diverse fields such as telecommunications, manufacturing and industrial engineering. The CPMP problem has been previously tackled by using distinct algorithmic approaches, among which we focus on evolutionary computation techniques. The work presented herein elaborates on these evolutionary computation algorithms when applied to the CPMP, by evaluating the performance of a novel grouping genetic algorithm (GGA) and a novel grouping harmony search approach (GHS). Both GGA and GHS are hybridized with a specially tailored local search procedure for enhancing the overall performance of the algorithm in the particular CPMP scenario under consideration. This manuscript delves into the main characteristics of the proposed GGA and GHS schemes by thoroughly describing the grouping encoding procedure, the evolutionary operators (GGA) and the improvisation process (GHS), the aforementioned local search procedure and a repairing technique that accounts for the feasibility of the solutions iteratively provided by both algorithms. The performance of the proposed algorithms is compared with that of several existing evolutionary-based algorithms for CPMP instances of varying size, based on which it is concluded that GGA and GHS dominate any other approaches published so far in the literature, specially when the size of the CPMP increases. The experimental section of the paper tries to evaluate the goodness of the grouping encoding, and also the differences in behavior between the GGA and GHS due to the meta-heuristic algorithm used.Item Cost-efficient deployment of multi-hop wireless networks over disaster areas using multi-objective meta-heuristics(2018-01-03) Bilbao, M. N.; Del Ser, Javier; Perfecto, C.; Salcedo-Sanz, S.; Portilla-Figueras, J. A.; IANowadays there is a global concern with the growing frequency and magnitude of natural disasters, many of them associated with climate change at a global scale. When tackled during a stringent economic era, the allocation of resources to efficiently deal with such disaster situations (e.g., brigades, vehicles and other support equipment for fire events) undergoes severe budgetary limitations which, in several proven cases, have lead to personal casualties due to a reduced support equipment. As such, the lack of enough communication resources to cover the disaster area at hand may cause a risky radio isolation of the deployed teams and ultimately fatal implications, as occurred in different recent episodes in Spain and USA during the last decade. This issue becomes even more dramatic when understood jointly with the strong budget cuts lately imposed by national authorities. In this context, this article postulates cost-efficient multi-hop communications as a technological solution to provide extended radio coverage to the deployed teams over disaster areas. Specifically, a Harmony Search (HS) based scheme is proposed to determine the optimal number, position and model of a set of wireless relays that must be deployed over a large-scale disaster area. The approach presented in this paper operates under a Pareto-optimal strategy, so a number of different deployments is then produced by balancing between redundant coverage and economical cost of the deployment. This information can assist authorities in their resource provisioning and/or operation duties. The performance of different heuristic operators to enhance the proposed HS algorithm are assessed and discussed by means of extensive simulations over synthetically generated scenarios, as well as over a more realistic, orography-aware setup constructed with LIDAR (Laser Imaging Detection and Ranging) data captured in the city center of Bilbao (Spain).Item Dandelion-encoded harmony search heuristics for opportunistic traffic offloading in synthetically modeled mobile networks(Springer Verlag, 2016) Perfecto, Cristina; Bilbao, Miren Nekane; Del Ser, Javier; Ferro, Armando; Salcedo-Sanz, Sancho; Geem, Zong Woo; Kim, Joong Hoon; IAThe high data volumes being managed by and transferred through mobile networks in the last few years are the main rationale for the upsurge of research aimed at finding efficient technical means to offload exceeding traffic to alternative communication infrastructures with higher transmission bandwidths. This idea is solidly buttressed by the proliferation of short-range wireless communication technologies (e.g.mobile devices with multiple radio interfaces), which can be conceived as available opportunistic hotspots to which the operator can reroute exceeding network traffic depending on the contractual clauses of the owner at hand. Furthermore, by offloading to such hotspots a higher effective coverage can be attained by those operators providing both mobile and fixed telecommunication services. In this context, the operator must decide if data generated by its users will be sent over conventional 4G+/4G/3G communication links, or if they will instead be offloaded to nearby opportunistic networks assuming a contractual cost penalty. Mathematically speaking, this problem can be formulated as a spanning tree optimization subject to cost-performance criteria and coverage constraints. This paper will elaborate on the efficient solving of this optimization paradigm by means of the Harmony Search meta-heuristic algorithm and the so-called Dandelion solution encoding, the latter allowing for the use of conventional meta-heuristic operators maximally preserving the locality of tree representations. The manuscript will discuss the obtained simulation results over different synthetically modeled setups of the underlying communication scenario and contractual clauses of the users.Item A grouping harmony search algorithm for assigning resources to users in WCDMA mobile networks(Springer Verlag, 2017) Aybar-Ruiz, Adrian; Cuadra, Lucas; Del Ser, Javier; Portilla-Figueras, Jose Antonio; Salcedo-Sanz, Sancho; Del Ser, Javier; IAThis paper explores the feasibility of a particular implementation of a Grouping Harmony Search (GHS) algorithm to assign resources (codes, aggregate capacity, power) to users in Wide-band Code Division Multiple Access (WCDMA) networks. We use a problem formulation that takes into account a detailed modeling of loads factors, including all the interference terms, which strongly depend on the assignment to be done. The GHS algorithm aims at minimizing a weighted cost function, which is composed of not only the detailed load factors but also resource utilization ratios (for aggregate capacity, codes, power), and the fraction of users without service. The proposed GHS is based on a particular encoding scheme (suitable for the problem formulation) and tailored Harmony Memory Considering Rate and Pitch Adjusting Rate processes. The experimental work shows that the proposed GHS algorithm exhibits a superior performance than that of the conventional approach, which minimizes only the load factors.Item A harmony search approach for the selective pick-up and delivery problem with delayed drop-off(Springer Verlag, 2016) Del Ser, Javier; Bilbao, Miren Nekane; Perfecto, Cristina; Salcedo-Sanz, Sancho; Geem, Zong Woo; Kim, Joong Hoon; IAIn the last years freight transportation has undergone a sharp increase in the scales of its underlying processes and protocols mainly due to the ever-growing community of users and the increasing number of on-line shopping stores. Furthermore, when dealing with the last stage of the shipping chain an additional component of complexity enters the picture as a result of the fixed availability of the destination of the good to be delivered. As such, business opening hours and daily work schedules often clash with the delivery times programmed by couriers along their routes. In case of conflict, the courier must come to an arrangement with the destination of the package to be delivered or, alternatively, drop it off at a local depot to let the destination pick it up at his/her time convenience. In this context this paper will formulate a variant of the so-called courier problem under economic profitability criteria including the cost penalty derived from the delayed drop-off. In this context, if the courier delivers the package to its intended destination before its associated deadline, he is paid a reward. However, if he misses to deliver in time, the courier may still deliver it at the destination depending on its availability or, alternatively, drop it off at the local depot assuming a certain cost. The manuscript will formulate the mathematical optimization problem that models this logistics process and solve it efficiently by means of the Harmony Search algorithm. A simulation benchmark will be discussed to validate the solutions provided by this meta-heuristic solver and to compare its performance to other algorithmic counterparts.Item Harmony search heuristics for quasi-asynchronous CDMA detection with M-PAM signalling(2010) Gil-Lopez, S.; Del Ser, J.; Garcia-Padrones, L.; IA; Centros PRE-FUSION TECNALIA - (FORMER)Focusing on CDMA (Code Division Multiple Access) uplink communications, this paper addresses the application of heuristic techniques to the multiple user detection problem when dealing with asynchrony between transmitters and bandwidth-limited PAM (Pulse AmplitudeModulation) signals. In such systems it is known that, even for the simplest case of binary modulated signals with perfectly synchronous transmitters, simple Single-User Detection (SUD) techniques (e.g. Rake receiver) are outperformed by Multiple-User Detection (MUD) schemes (based on the Maximum-Likelihood - ML - criteria), at a computational cost exponentially increasing with the number of users. Consequently, Genetic Algorithms (GA) have been extensively studied during the last decade as a means to alleviate the computational complexity of CDMA MUD detectors while incurring, at the same time, in a negligible error rate penalty. In this manuscript, a novel heuristic approach inspired in the recent Harmony Search algorithm will be shown to provide a faster convergence and a better error rate performance than conventional GA's in presence of inter-user asynchrony in bandwidth-limited CDMA communications, specially when the complexity of the scenario increases.Item A hybrid harmony search algorithm for the spread spectrum radar polyphase codes design problem(2012-09-15) Gil-López, Sergio; Ser, Javier Del; Salcedo-Sanz, Sancho; Pérez-Bellido, Ángel M.; Cabero, José María; Portilla-Figueras, José A.; IA; Tecnalia Research & InnovationIn this paper we present the application of a hybrid harmony search (HS) algorithm to the Spread-Spectrum Radar Polyphase (SSRP) codes design. Such a design can be formulated as a non-linear max-min optimization problem, hard to be solved using classical numerical techniques. Soft-computing approaches have then been successfully applied to solve the SSRP in the past, such as evolutionary computation techniques, variable neighborhood approaches or tabu search algorithms. In this paper we elaborate on the proposed hybrid HS approach, which consists of a naive implementation of the HS algorithm along with an adaptive-step gradient-guided local search procedure. Intensive computer simulations show that the proposed hybrid HS algorithm is able to outperform existing algorithms for the SSRP design problem (including the best reported so far), with significant differences in large-size SSRP instances.Item Iterative power and subcarrier allocation in rate-constrained orthogonal multi-carrier downlink systems based on hybrid harmony search heuristics(2011-08) Del Ser, Javier; Bilbao, Miren Nekane; Gil-López, Sergio; Matinmikko, Marja; Salcedo-Sanz, Sancho; IAThis paper presents a novel iterative hybrid algorithm for subcarrier and power allocation in a cognitive orthogonal frequency division multiple access (OFDMA) downlink. In the considered setup a primary base station forwards information to K distant receivers by using a single OFDM waveform, whereas a secondary base station subject to stringent per-user rate constraints interferes with the former by sending information from users to the same set of destinations. Power and user allocation at both base stations is jointly performed by the proposed algorithm to maximize the overall throughput of the setup while satisfying, at the same time, the imposed rate constraints. Our proposal, which stems from an hybridization of the harmony search (HS) and differential evolution (DE) algorithms along with a greedy local repair method, is shown through computer simulations over the extended vehicular A ITU channel model to be an effective and practical resource allocation procedure for cognitive OFDMA downlinks.Item A novel grouping harmony search algorithm for clustering problems(Springer Verlag, 2017) Landa-Torres, Itziar; Manjarres, Diana; Gil-López, Sergio; Del Ser, Javier; Sanz, Sancho Salcedo; Del Ser, Javier; Tecnalia Research & Innovation; IAThe problem of partitioning a data set into disjoint groups or clusters of related items plays a key role in data analytics, in particular when the information retrieval becomes crucial for further data analysis. In this context, clustering approaches aim at obtaining a good partition of the data based on multiple criteria. One of the most challenging aspects of clustering techniques is the inference of the optimal number of clusters. In this regard, a number of clustering methods from the literature assume that the number of clusters is known a priori and subsequently assign instances to clusters based on distance, density or any other criterion. This paper proposes to override any prior assumption on the number of clusters or groups in the data at hand by hybridizing the grouping encoding strategy and the Harmony Search (HS) algorithm. The resulting hybrid approach optimally infers the number of clusters by means of the tailored design of the HS operators, which estimates this important structural clustering parameter as an implicit byproduct of the instance-to-cluster mapping performed by the algorithm. Apart from inferring the optimal number of clusters, simulation results verify that the proposed scheme achieves a better performance than other naïve clustering techniques in synthetic scenarios and widely known data repositories.Item A novel heuristic approach for distance- and connectivity-based multihop node localization in wireless sensor networks(2013-01) Manjarres, Diana; Del Ser, Javier; Gil-Lopez, Sergio; Vecchio, Massimo; Landa-Torres, Itziar; Lopez-Valcarce, Roberto; IA; Tecnalia Research & InnovationThe availability of accurate location information of constituent nodes becomes essential in many applications of wireless sensor networks. In this context, we focus on anchor-based networks where the position of some few nodes are assumed to be fixed and known a priori, whereas the location of all other nodes is to be estimated based on noisy pairwise distance measurements. This localization task embodies a non-convex optimization problem which gets even more involved by the fact that the network may not be uniquely localizable, especially when its connectivity is not sufficiently high. To efficiently tackle this problem, we present a novel soft computing approach based on a hybridization of the Harmony Search (HS) algorithm with a local search procedure that iteratively alleviates the aforementioned non-uniqueness of sparse network deployments. Furthermore, the areas in which sensor nodes can be located are limited by means of connectivity-based geometrical constraints. Extensive simulation results show that the proposed approach outperforms previously published soft computing localization techniques in most of the simulated topologies. In particular, to assess the effectiveness of the technique, we compare its performance, in terms of Normalized Localization Error (NLE), to that of Simulated Annealing (SA)-based and Particle Swarm Optimization (PSO)-based techniques, as well as a naive implementation of a Genetic Algorithm (GA) incorporating the same local search procedure here proposed. Non-parametric hypothesis tests are also used so as to shed light on the statistical significance of the obtained results.Item On the application of a novel Grouping Harmony Search algorithm to the Switch Location Problem(2010) Gil-Lopez, Sergio; Del Ser, Javier; Landa, Itziar; Garcia-Padrones, Laura; Salcedo-Sanz, Sancho; Portilla-Figueras, Jose A.; IA; Tecnalia Research & Innovation; Centros PRE-FUSION TECNALIA - (FORMER)This paper presents the adaptation of a novel heuristic algorithm to the Switch Location Problem (SLP), a NP-hard problem where a set of distributed terminals, with distinct rate demands, is to be assigned to a fixed number of concentrators subject to capacity constraints. Each terminal must be assigned to one and only one concentrator while keeping the overall rate demanded from such concentrator below its maximum capacity. Related literature demonstrates that the inclusion of the so-called grouping concept into the allocation algorithm is essential when dealing with this specific kind of optimization scenarios. As such, previous studies introducing Grouped Genetic Algorithms (GGA) combined with local search and/or repair methods show that their proposed allocation procedure alleviates significantly the computational complexity required by an exhaustive search strategy for the SLP problem, while outperforming other hybrid heuristic algorithms. In this manuscript, a novel Grouped Harmony Search (GHS) algorithm designed for the SLP paradigm is hybridized with both a local search method and a technique aimed at repairing the solutions iteratively supplied by the heuristic process. Extensive Monte Carlo simulations assess that our proposal provides faster convergence rate and better statistical performance than the previously proposed GGA, specially when the size of the SLP scenario increases.Item One-way urban traffic reconfiguration using a multi-objective harmony search approach(2013-07) Salcedo-Sanz, S.; Manjarrés, D.; Pastor-Sánchez, Á; Del Ser, J.; Portilla-Figueras, J. A.; Gil-López, S.; IAThe use of intelligent optimization systems has been a major topic of research in the last few years for improving the existing urban infrastructure, the traffic optimization and the mobility of citizens. These techniques are of great importance in the analysis and optimization of transportation networks, as well as their re-organization to improve users' mobility. In this paper we focus on the reconfiguration of one-way roads in a city after the occurrence of a major problem (e.g. a long-term road cut) in order to provide alternative routes that guarantee the mobility of citizens. In this manuscript a novel definition of this problem is formulated, for whose efficient resolution a novel two-objective approach based on the harmony search (HS) algorithm is proposed. The effectiveness of this proposal is tested in several synthetic instances, along with a real scenario in a city near Madrid, Spain. Extensive simulation results have been analyzed to verify that our proposal obtains excellent results in all the considered scenarios.Item Optimal Phase Swapping in Low Voltage Distribution Networks Based on Smart Meter Data and Optimization Heuristics(Springer Verlag, 2017) Mendia, Izaskun; Gil-López, Sergio; Del Ser, Javier; Bordagaray, Ana González; Prado, Jesús García; Vélez, Manuel; Del Ser, Javier; Tecnalia Research & Innovation; IAIn this paper a modified version of the Harmony Search algorithm is proposed as a novel tool for phase swapping in Low Voltage Distribution Networks where the objective is to determine to which phase each load should be connected in order to reduce the unbalance when all phases are added into the neutral conductor. Unbalanced loads deteriorate power quality and increase costs of investment and operation. A correct assignment is a direct, effective alternative to prevent voltage peaks and network outages. The main contribution of this paper is the proposal of an optimization model for allocating phases consumers according to their individual consumption in the network of low-voltage distribution considering mono and bi-phase connections using real hourly load patterns, which implies that the computational complexity of the defined combinatorial optimization problem is heavily increased. For this purpose a novel metric function is defined in the proposed scheme. The performance of the HS algorithm has been compared with classical Genetic Algorithm. Presented results show that HS outperforms GA not only on terms of quality but on the convergence rate, reducing the computational complexity of the proposed scheme while provide mono and bi phase connections.Item PLAHS: A Partial Labelling Autonomous Hyper-heuristic System for Industry 4.0 with application on classification of cold stamping process[Formula presented](2023-11) Navajas-Guerrero, Adriana; Portillo, Eva; Manjarres, Diana; IAIn real-life industry it is difficult to have fully-labelled datasets due to lack of time, resources or knowledge. In this sense, this paper proposes the design and development of a Partial Labelling Autonomous Hyper-heuristic System PLAHS, a solution that autonomously labels partially labelled databases and evaluates the yielded labelling solution by means of a novel Trustworthiness Metric (TM). The proposal combines a hyper-heuristic inspired approach with a Semi Supervised Learning Clustering (SSLC) methodology that optimizes the parameters of different clustering algorithms, based on a novel semi-supervised metric named Partially Supervised Optimization Metric (PSOM). The proposal has been tested with promising and excellent results on both a real use case for labelling work orders in a cold stamping press, and 13 databases from the UCI (multivariate data) and UCR (time series data) repositories.Item Underwater Robot Task Planning Using Multi-Objective Meta-Heuristics(2017-04-04) Landa-Torres, Itziar; Manjarres, Diana; Bilbao, Sonia; Del Ser, Javier; Tecnalia Research & Innovation; IA; BIGDATARobotics deployed in the underwater medium are subject to stringent operational conditions that impose a high degree of criticality on the allocation of resources and the schedule of operations in mission planning. In this context the so-called cost of a mission must be considered as an additional criterion when designing optimal task schedules within the mission at hand. Such a cost can be conceived as the impact of the mission on the robotic resources themselves, which range from the consumption of battery to other negative effects such as mechanic erosion. This manuscript focuses on this issue by devising three heuristic solvers aimed at efficiently scheduling tasks in robotic swarms, which collaborate together to accomplish a mission, and by presenting experimental results obtained over realistic scenarios in the underwater environment. The heuristic techniques resort to a Random-Keys encoding strategy to represent the allocation of robots to tasks and the relative execution order of such tasks within the schedule of certain robots. The obtained results reveal interesting differences in terms of Pareto optimality and spread between the algorithms considered in the benchmark, which are insightful for the selection of a proper task scheduler in real underwater campaigns.Item Wireless network optimization for massive V2I data collection using multiobjective harmony search heuristics(Springer Verlag, 2017) Sobron, Iker; Alonso, Borja; Vélez, Manuel; Del Ser, Javier; Del Ser, Javier; IAThis paper proposes to improve the efficiency of the deployment of wireless network infrastructure for massive data collection from vehicles over regional areas. The increase in the devices that are carried by vehicles makes it especially interesting being able to gain access to that data. From a decisional point of view, this collection strategy requires defining a wireless Vehicular-to-Infrastructure (V2I) network that jointly optimizes the level of service and overall CAPEX/OPEX costs of its deployment. Unfortunately, it can be intuitively noted that both optimization objectives are connecting with one another: adding more equipment will certainly increase the level of service (i.e. coverage) of the network, but costs of the deployment will rise accordingly. A decision making tool blending together both objectives and inferring therefrom a set of Pareto-optimal deployments would be of utmost utility for stakeholders in their process of provisioning budgetary resources for the deployment. This work will explore the extent to which a multi-objective Harmony Search algorithm can be used to compute the aforementioned Pareto-optimal set of deployment by operating on two different optimization variables: the geographical position on which wireless receivers are to be deployed and their type, which determines not only their coverage range but also their bandwidth and cost. In particular we will utilize a non-dominated sorting strategy criterion to select the harmonies (solution vectors) evolved by Harmony Search heuristics.