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Academic literature on the topic 'Neighbourhood algorithm'

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Published: 4 June 2021
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Journal articles on the topic "Neighbourhood algorithm"

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Wightman, Rick A., and Emin Z. Baskent. "Forest neighbourhoods for timber harvest scheduling." Forestry Chronicle 70, no. 6 (December 1, 1994): 768–72. http://dx.doi.org/10.5558/tfc70768-6.

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Forest management involves exploring through time the scheduling opportunities for timber and non-timber values within a forest. The ability to identify and form neighbourhoods — areas of suitable stand conditions and locations — is critical to this endeavour. This paper presents a GIS-based algorithm for identifying and forming forest neighbourhoods suitable for timber harvest scheduling. The resulting neighbourhoods are contiguous and overlapping, composed of stands sharing similar attributes. Similarity is based on a definable similarity list where stand conditions closest to one another in the list are most similar to one another. The algorithm is demonstrated with a single stand example and then a small forest example. Control of neighbourhood size is limited using a vector data model, except in forests composed of small stands. The examples illustrate that neighbourhood inclusion is dependent on both a forest stand's condition and relative position in the forest. The paper concludes with suggestions for further development of the algorithm. Key words: timber harvest scheduling, forest management, spatial modelling, GIS, neighbourhoods
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Chmiel, W., P. Kadłuczka, J. Kwiecień, and B. Filipowicz. "A comparison of nature inspired algorithms for the quadratic assignment problem." Bulletin of the Polish Academy of Sciences Technical Sciences 65, no. 4 (August 1, 2017): 513–22. http://dx.doi.org/10.1515/bpasts-2017-0056.

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AbstractThis paper presents an application of the ant algorithm and bees algorithm in optimization of QAP problem as an example of NP-hard optimization problem. The experiments with two types of algorithms: the bees algorithm and the ant algorithm were performed for the test instances of the quadratic assignment problem from QAPLIB, designed by Burkard, Karisch and Rendl. On the basis of the experiments results, an influence of particular elements of algorithms, including neighbourhood size and neighbourhood search method, will be determined.
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QIU, KE. "ON A UNIFIED NEIGHBOURHOOD BROADCASTING SCHEME FOR INTERCONNECTION NETWORKS." Parallel Processing Letters 17, no. 04 (December 2007): 425–37. http://dx.doi.org/10.1142/s0129626407003137.

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The neighbourhood broadcasting problem in an interconnection network is defined as sending a fixed sized message from the source node to all its neighbours in a single-port model. Previously, this problem has been studied for several interconnection networks including the hypercube and the star. The objective of such works has been to minimize the total number of steps required for the neighbourhood broadcasting algorithms. Here, we first use a general neighbourhood broadcasting scheme to develop a neighbourhood broadcasting algorithm for the star interconnection network that is asymptotically optimal, conceptually simple, and easy to implement since routing for all nodes involved is uniform. It uses the cycle structures of the star graph as well as the standard technique of recursive doubling. We then show that the scheme for the star network is general enough to be applied to a broader family of interconnection networks such as the pancake interconnection network for which no previous neighbourhood broadcasting algorithm is known, resulting in asymptotically optimal algorithms. Finally, we use this scheme to develop neighbourhood broadcasting algorithms for multiple messages for several interconnection networks.
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Wang, Y. D., X. C. Lu, and J. R. Shen. "Improved Genetic Algorithm (VNS-GA) using polar coordinate classification for workload balanced multiple Traveling Salesman Problem (mTSP)." Advances in Production Engineering & Management 16, no. 2 (June 25, 2021): 173–84. http://dx.doi.org/10.14743/apem2021.2.392.

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The multiple traveling salesman problem (mTSP) is an extension of the traveling salesman problem (TSP), which has wider applications in real life than the traveling salesman problem such as transportation and delivery, task allocation, etc. In this paper, an improved genetic algorithm (VNS-GA) that uses polar coordinate classification to generate the initial solutions is proposed. It integrates the variable neighbourhood algorithm to solve the multiple objective optimization of the mTSP with workload balance. Aiming to workload balance, the first design of this paper is about generating initial solutions based on the polar coordinate classification. Then a distance comparison insertion operator is designed as a neighbourhood action for allocating paths in a targeted manner. Finally, the neighbourhood descent process in the variable neighbourhood algorithm is fused into the genetic algorithm for the expansion of search space. The improved algorithm is tested on the TSPLIB standard data set and compared with other genetic algorithms. The results show that the improved genetic algorithm can increase computational efficiency and obtain a better solution for workload balance and this algorithm has wild applications in real life such as multiple robots task allocation, school bus routing problem and other optimization problems.
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Wang, Y. D., X. C. Lu, and J. R. Shen. "Improved Genetic Algorithm (VNS-GA) using polar coordinate classification for workload balanced multiple Traveling Salesman Problem (mTSP)." Advances in Production Engineering & Management 16, no. 2 (June 25, 2021): 173–84. http://dx.doi.org/10.14743/apem2021.2.392.

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The multiple traveling salesman problem (mTSP) is an extension of the traveling salesman problem (TSP), which has wider applications in real life than the traveling salesman problem such as transportation and delivery, task allocation, etc. In this paper, an improved genetic algorithm (VNS-GA) that uses polar coordinate classification to generate the initial solutions is proposed. It integrates the variable neighbourhood algorithm to solve the multiple objective optimization of the mTSP with workload balance. Aiming to workload balance, the first design of this paper is about generating initial solutions based on the polar coordinate classification. Then a distance comparison insertion operator is designed as a neighbourhood action for allocating paths in a targeted manner. Finally, the neighbourhood descent process in the variable neighbourhood algorithm is fused into the genetic algorithm for the expansion of search space. The improved algorithm is tested on the TSPLIB standard data set and compared with other genetic algorithms. The results show that the improved genetic algorithm can increase computational efficiency and obtain a better solution for workload balance and this algorithm has wild applications in real life such as multiple robots task allocation, school bus routing problem and other optimization problems.
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Kazakovtsev, Lev, Dmitry Stashkov, Mikhail Gudyma, and Vladimir Kazakovtsev. "Algorithms with greedy heuristic procedures for mixture probability distribution separation." Yugoslav Journal of Operations Research 29, no. 1 (2019): 51–67. http://dx.doi.org/10.2298/yjor171107030k.

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For clustering problems based on the model of mixture probability distribution separation, we propose new Variable Neighbourhood Search algorithms (VNS) and evolutionary genetic algorithms (GA) with greedy agglomerative heuristic procedures and compare them with known algorithms. New genetic algorithms implement a global search strategy with the use of a special crossover operator based on greedy agglomerative heuristic procedures in combination with the EM algorithm (Expectation Maximization). In our new VNS algorithms, this combination is used for forming randomized neighbourhoods to search for better solutions. The results of computational experiments made on classical data sets and the testings of production batches of semiconductor devices shipped for the space industry demonstrate that new algorithms allow us to obtain better results, higher values of the log likelihood objective function, in comparison with the EM algorithm and its modifications.
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Heinz, Jeffrey. "On the role of locality in learning stress patterns." Phonology 26, no. 2 (August 2009): 303–51. http://dx.doi.org/10.1017/s0952675709990145.

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AbstractThis paper presents a previously unnoticed universal property of stress patterns in the world's languages: they are, for small neighbourhoods, neighbourhood-distinct. Neighbourhood-distinctness is a locality condition defined in automata-theoretic terms. This universal is established by examining stress patterns contained in two typological studies. Strikingly, many logically possible – but unattested – patterns do not have this property. Not only does neighbourhood-distinctness unite the attested patterns in a non-trivial way, it also naturally provides an inductive principle allowing learners to generalise from limited data. A learning algorithm is presented which generalises by failing to distinguish same-neighbourhood environments perceived in the learner's linguistic input – hence learning neighbourhood-distinct patterns – as well as almost every stress pattern in the typology. In this way, this work lends support to the idea that properties of the learner can explain certain properties of the attested typology, an idea not straightforwardly available in optimality-theoretic and Principle and Parameter frameworks.
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Zhang, Da Ming, Hua Yong Liu, Juan Chen, and Lu Li. "Two-Dimensional Extensions of Neighborhood Preserving Embedding." Applied Mechanics and Materials 198-199 (September 2012): 420–25. http://dx.doi.org/10.4028/www.scientific.net/amm.198-199.420.

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Neighbourhood Preserving Embedding (NPE) is a novel subspace learning algorithm, which aims at preserving the local neighbourhood structure on the data manifold and is a linear approximation to Locally Linear Embedding (LLE). However, in typical image recognition in 1D vectors space, where the number of data samples is smaller than the dimension of data space, suffering from the singularity problem of matrix, NPE algorithm cannot be implemented directly. In this paper, we investigate NPE directly on image matrix for image recognition. The proposed two-dimensional neighbourhood preserving embedding (2DNPE) and bilateral two-dimensional neighbourhood preserving embedding (B2DNPE) algorithms are all based directly on 2D image matrices rather than on 1D vectors as NPE does, thus the problem of singularity confronted in 1D case is overcome. 2DNPE performs compression only in row direction, while B2DNPE performs compression both in row and in column direction. The relation of them to 2DLPP (B2DLPP) are also presented. The proposed algorithms are evaluated on ORL face database and handwritten digits database.
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Yan, Xingya, Jian Lei, and Zhi Zhao. "Multidirectional Gradient Neighbourhood-Weighted Image Sharpness Evaluation Algorithm." Mathematical Problems in Engineering 2020 (April 7, 2020): 1–7. http://dx.doi.org/10.1155/2020/7864024.

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Aiming at the problem that the image sharpness evaluation algorithm in the photoelectric system has a slow speed in actual processing and is severely disturbed by noise, an improved image sharpness evaluation algorithm is proposed by combining multiscale decomposition tools and multidirectional gradient neighbourhood weighting. This paper applies non-subsampled shearlet transform (NSST) to perform multiscale transformation of the input images, obtaining high-frequency sub-band images and low-frequency sub-band images. In order to enhance the detection of the edge orientation of images, multidirectional gradient processing of the image matrix is added to each sub-band image. In addition, the weight corresponding to the current pixel is obtained by calculating the inverse ratio of the gradient of each direction and the distance of the center pixel. Through calculating the ratio of the gradient neighbourhood weighting operators of high-frequency sub-band images and low-frequency sub-band images, the image sharpness evaluation value can be acquired further. Moreover, the image sequence collected by a certain type of photoelectric system is selected as the image sequence of the noisy real environment for simulation experiments and compared with the current mainstream algorithms. Finally, the experimental draws a conclusion that compared with the mainstream evaluation algorithms, the evaluation results of the proposed method perform better in terms of steepness, sensitivity, and flat area fluctuation, it can better suppress noise and improve accuracy, and its running speed meets the basic requirements of the image sharpness evaluation algorithm.
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Mohammed Jabbar, Ayad, Ku Ruhana Ku-Mahamud, and Rafid Sagban. "An improved ACS algorithm for data clustering." Indonesian Journal of Electrical Engineering and Computer Science 17, no. 3 (March 1, 2020): 1506. http://dx.doi.org/10.11591/ijeecs.v17.i3.pp1506-1515.

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<span lang="EN-GB">Data clustering is a data mining technique that discovers hidden patterns by creating groups (clusters) of objects. Each object in every cluster exhibits sufficient similarity to its neighbourhood, whereas objects with insufficient similarity are found in other clusters. Data clustering techniques minimise intra-cluster similarity in each cluster and maximise inter-cluster dissimilarity amongst different clusters. Ant colony optimisation for clustering (ACOC) is a swarm algorithm inspired by the foraging behaviour of ants. This algorithm minimises deterministic imperfections in which clustering is considered an optimisation problem. However, ACOC suffers from high diversification in which the algorithm cannot search for best solutions in the local neighbourhood. To improve the ACOC, this study proposes a modified ACOC, called M-ACOC, which has a modification rate parameter that controls the convergence of the algorithm. Comparison of the performance of several common clustering algorithms using real-world datasets shows that the accuracy results of the proposed algorithm surpasses other algorithms. </span>
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Dissertations / Theses on the topic "Neighbourhood algorithm"

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Ahmad, Siti. "A study of search neighbourhood in the bees algorithm." Thesis, Cardiff University, 2012. http://orca.cf.ac.uk/19127/.

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The Bees Algorithm, a heuristic optimisation procedure that mimics bees foraging behaviour, is becoming more popular among swarm intelligence researchers. The algorithm involves neighbourhood and global search and is able to find promising solutions to complex multimodal optimisation problems. The purpose of neighbourhood search is to intensify the search effort around promising solutions, while global search is to enable avoidance of local optima. Despite numerous studies aimed at enhancing the Bees Algorithm, there have not been many attempts at studying neighbourhood search. This research investigated different kinds of neighbourhoods and their effects on neighbourhood search. First, the adaptive enlargement of the search neighbourhood was proposed. This idea was implemented in the Bees Algorithm and tested on a set of mathematical benchmarks. The modified algorithm was also tested on single objective engineering design problems. The experimental results obtained confirmed that the adaptive enlargement of the search neighbourhood improved the performance of the proposed algorithm. Normally, a symmetrical search neighbourhood is employed in the Bees Algorithm. As opposed to this practice, an asymmetrical search neighbourhood was tried in this work to determine the significance of neighbourhood symmetry. In addition to the mathematical benchmarks, the algorithm with an asymmetrical search neighbourhood was also tested on an engineering design problem. The analysis verified that under certain measurements of asymmetry, the proposed ii algorithm produced a similar performance as that of the Bees Algorithm. For this reason, it was concluded that users were free to employ either a symmetrical or an asymmetrical search neighbourhood in the Bees Algorithm. Finally, the combination of adaptive enlargement and reduction of the search neighbourhood was presented. In addition to the above mathematical benchmarks and engineering design problems, a multi-objective design optimisation exercise with constraints was selected to demonstrate the performance of the modified algorithm. The experimental results obtained showed that this combination was beneficial to the proposed algorithm.
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Marson-Pidgeon, Katrina Ann, and katrina marson-pidgeon@anu edu au. "Seismogram synthesis for teleseismic events with application to source and structural studies." The Australian National University. Research School of Earth Sciences, 2001. http://thesis.anu.edu.au./public/adt-ANU20010925.152548.

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The aim of this thesis is to develop procedures for the modelling and inversion of teleseismic P and S waveforms which are as flexible as possible. This flexibility is necessary in order to obtain accurate source depth and mechanism estimates for small to moderate size events, such as those that are relevant in the context of monitoring the Comprehensive Nuclear-Test-Ban Treaty (CTBT). ¶ The main challenge for extending source depth and mechanism inversion methods to smaller events is to ensure that sufficiently accurate synthetic seismograms are available for comparison with observed records. An accurate phase-adaptive reflectivity method has therefore been developed, against which the performance of less computationally intensive approximations can be judged. The standard reflectivity method has been modified to allow for different crustal and upper mantle structures at the source and receiver, and the full effects of reverberations and conversions in these structures can be allowed for. Core reflections and refractions can also be included; these phases can become important at certain distance ranges. A slowness bundle approach has been developed, where a restricted slowness integration about the geometric slowness for the direct wave is undertaken at each frequency, allowing accurate results to be obtained whilst avoiding the expense of a full reflectivity technique. ¶ Inversion using the neighbourhood algorithm (NA) is performed for source depth, mechanism and time function, by modelling direct P and S and their surface reflections (pP, sP and pS, sS) at teleseismic distances. Both SV and SH data are exploited in the inversion, in addition to P data, in order to obtain improved constraints on the source mechanism, including any isotropic component. Good results are obtained using a simple generalised ray scheme, however, the use of a flexible derivative-free inversion method means that more accurate synthetics are able to be used in the inversion where appropriate. The NA makes use of only the rank of the data misfits, so that it is possible to employ any suitable misfit criterion. In the few cases where control on the source mechanism is limited, good depth resolution is still usually obtained. ¶The structures near the source and receiver play an important role in shaping the detail of the teleseismic waveforms. Although reasonable results can be achieved with simple synthetics and a standard velocity model, significant improvement can be made by modifying the representation of structure near the source and receiver. In the case of sub-oceanic events it is important to allow for the effects of water reverberations. The crustal structure near the receiver can also have quite a large influence on the waveforms through reverberations and conversions. This is exploited in receiver function inversion, which is again accomplished using the NA approach.
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Bashir, Bushra. "Contribution to modeling and optimization of home healthcare." Thesis, Clermont-Ferrand 2, 2013. http://www.theses.fr/2013CLF22391/document.

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A healthcare network or health system consists of all organizations, actions and people who participate to promote, restore or maintain people’s health. The health care systems in many developed countries are facing increasing costs. The major reason is the changing age distribution of the population with more elderly people in need of support. Increasing healthcare costs has created new alternatives to traditional hospitalization in which one is Home Health Care (HHC). Home health care or domiciliary care is the provision of health care and assistance to people in their own homes, according to a formal assessment of their needs. HHC has attained a specific place in healthcare network. HHC programs have now been successfully implemented in many countries. The purpose of HHC is to provide the care and support needed to assist patients to live independently in their own homes. HHC is primarily performed by means of personal visitations of healthcare workers to patients in their homes, where they provide care assistance according to patients’ needs. In this thesis we have considered different aspects of planning problems for home health care services. The efficient use of resources is necessary in continuous healthcare services. To meet the increased demand of HHC, operation research specialist can play an important role by solving the various combinatorial optimization problems arising in HHC. These problems can be tactical, strategic or operational with respect to planning horizon. Strategic problems are those which help in attaining long term goals or objectives, e.g. higher level of quality for HHC patients and efficient use of resources. These strategic objectives can be achieved through tactical i.e. medium term panning and operational planning i.e. short term planning. The main purpose of our thesis is to identify these potential optimization problems and solve them via recent metaheuristics. HHC is an alternative to traditional hospitalization and has got a significant share in the organization of healthcare in developed countries. The change in aging demographics, recent development in technology and the increase in the demand of healthcare services are major reasons for this rapid growth. Some studies show HHC as a tool to reduce costs of care, which is a major preoccupation in developed countries. Some others reveal that it leads to the improvement of patients’ satisfaction without increasing the resources. Home health care, i.e. visiting and nursing patients in their homes, is a flourishing realm in the medical industry. The number of companies has grown largely both in public and private sectors. The staffing needs for HHC companies have been expanded as well. Also they face the problem of assigning geographically dispersed patients to home healthcare workers and preparing daily schedules for these workers. The challenge of this problem is to combine aspects of vehicle routing and staff rostering. Both of them are well known NP- hard combinatorial optimization problems, it means the amount of computational time required to find solution increases exponentially with problem size. Home healthcare workers scheduling problem is difficult to solve optimally due to presence of large number of constraints. These are two types of constraints: hard constraints and soft constraints. The hard constraints are the restrictions to be fulfilled for the schedules to be applicable and soft constraints are preferences to improve the quality of these schedules. (...)
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Danloup, Nicolas. "Les problèmes de collectes et livraisons avec collaboration et transbordements : modélisations et méthodes approchées." Thesis, Artois, 2016. http://www.theses.fr/2016ARTO0203/document.

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La logistique collaborative est récemment devenue un élément important pour beaucoup d'entreprises afin d'améliorer l'efficacité de leur chaîne logistique. Dans cette thèse, nous étudions les possibilités offertes par les problèmes de collectes et livraisons pour améliorer les performances des chaînes logistiques grâce au transport collaboratif. La thèse est inscrite dans un projet européen nommé SCALE (Step Change in Agri-food Logistics Ecosystem). Dans un premier temps, deux métaheuristiques sont proposées et étudiées pour résoudre le problème de collectes et livraisons avec transbordements. Celles-ci sont comparées aux travaux de la littérature et permettent d’améliorer les résultats sur certaines instances. Dans un deuxième temps, un modèle pour un problème de collectes et livraisons (PDVRP) est proposé. Celui-ci est utilisé pour étudier les bénéfices de la collaboration sur le transport. Il est appliqué sur des données générées aléatoirement et sur des données réelles issues du projet SCALE. Enfin troisièmement, un modèle pour un PDVRP particulier est présenté. Dans ce modèle, les marchandises doivent passer par exactement deux points de transbordement entre les points de collecte et les points de livraison. Ce problème est inspiré d'une seconde étude de cas réalisée dans le cadre du projet SCALE. Ceci permet de mettre en évidence l’intérêt de la collaboration et du transbordement dans le domaine du transport de marchandises
Collaborative logistics have become recently an important element for many companies to improve their supply chains efficiency. In this thesis, we study pickup and delivery problems to improve supply chains efficiency thanks to collaborative transportation. The thesis was part of the European project SCALE (Step Change in Agri-food Logistics Ecosystem). Firstly, two metaheuristics are proposed and studied to solve the Pickup and Delivery Problem with Transshipments. These metaheuristics are compared with literature works and the results of several instances are improved. Secondly, a mathematical model for a pickup and delivery problem (PDVRP) is proposed. This model is used to study the benefits of collaboration on transportation. It is applied on random data and on a case study from SCALE with real data. Finally, a model for a particular PDVRP is presented. In this model, the shipments have to cross exactly two transshipments nodes between their pickup and delivery points. This problem is inspired by a second case study made during the project SCALE. This allows to highlight the importance of collaboration and transshipment in the field of goods transportations
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Rayar, Frédéric. "Exploration interactive, incrémentale et multi-niveau de larges collections d'images." Thesis, Tours, 2016. http://www.theses.fr/2016TOUR4012/document.

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Les travaux de recherche présentés et discutés dans cette thèse s’intéressent aux grandes collections d’images numériques. Plus particulièrement, nous cherchons à donner à un utilisateur la possibilité d’explorer ces collections d’images, soit dans le but d’en extraire de l’information et de la connaissance, soit de permettre une certaine sérendipité dans l’exploration. Ainsi, cette problématique est abordée du point de vue de l’analyse et l’exploration interactive des données. Nous tirons profit du paradigme de navigation par similarité et visons à respecter simultanément les trois contraintes suivantes : (i) traiter de grandes collections d’images, (ii) traiter des collections dont le nombre d’images ne cesse de croître au cours du temps et (iii) donner des moyens d’explorer interactivement des collections d’images. Pour ce faire, nous proposons d’effectuer une étude conjointe de l’indexation et de la visualisation de grandes collections d’images qui s’agrandissent au cours du temps
The research work that is presented and discussed in this thesis focuses on large and evergrowing image collections. More specifically, we aim at providing one the possibility to explore such image collections, either to extract some kind of information and knowledge, or to wander in the collections. This thesis addresses this issue from the perspective of Interactive Data Exploration and Analytics. We take advantage of the similarity-based image collection browsing paradigm and aim at meeting simultaneously the three following constraints: (i) handling large image collections, up to millions of images, (ii) handling dynamic image collections, to deal with ever-growing image collections, and (iii) providing interactive means to explore image collections. To do so, we jointly study the indexing and the interactive visualisation of large and ever-growing image collections
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Derrick, Deborah Chippington. "Models, methods and algorithms for supply chain planning." Thesis, Brunel University, 2011. http://bura.brunel.ac.uk/handle/2438/6024.

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An outline of supply chains and differences in the problem types is given. The motivation for a generic framework is discussed and explored. A conceptual model is presented along with it application to real world situations; and from this a database model is developed. A MIP and CP implementations are presented; along with alternative formulation which can be use to solve the problems. A local search solution algorithm is presented and shown to have significant benefits. Problem instances are presented which are used to validate the generic models, including a large manufacture and distribution problem. This larger problem instance is not only used to explore the implementation of the models presented, but also to explore the practically of the use of alternative formulation and solving techniques within the generic framework and the effectiveness of such methods including the neighbourhood search solving method. A stochastic dimension to the generic framework is explored, and solution techniques for this extension are explored, demonstrating the use of solution analysis to allow problem simplification and better solutions to be found. Finally the local search algorithm is applied to the larger models that arise from inclusion of scenarios, and the methods is demonstrated to be powerful for finding solutions for these large model that were insoluble using the MIP on the same hardware.
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Remde, Stephen M., Peter I. Cowling, Keshav P. Dahal, and N. J. Colledge. "Exact/heuristic hybrids using rVNS and hyperheuristics for workforce scheduling." Springer-Verlag, 2007. http://hdl.handle.net/10454/2510.

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In this paper we study a complex real-world workforce scheduling problem. We propose a method of splitting the problem into smaller parts and solving each part using exhaustive search. These smaller parts comprise a combination of choosing a method to select a task to be scheduled and a method to allocate resources, including time, to the selected task. We use reduced Variable Neighbourhood Search (rVNS) and hyperheuristic approaches to decide which sub problems to tackle. The resulting methods are compared to local search and Genetic Algorithm approaches. Parallelisation is used to perform nearly one CPU-year of experiments. The results show that the new methods can produce results fitter than the Genetic Algorithm in less time and that they are far superior to any of their component techniques. The method used to split up the problem is generalisable and could be applied to a wide range of optimisation problems.
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Ågren, Magnus. "Set Constraints for Local Search." Doctoral thesis, Uppsala universitet, Avdelningen för datalogi, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-8373.

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Combinatorial problems are ubiquitous in our society and solving such problems efficiently is often crucial. One technique for solving combinatorial problems is constraint-based local search. Its compositional nature together with its efficiency on large problem instances have made this technique particularly attractive. In this thesis we contribute to simplifying the solving of combinatorial problems using constraint-based local search. To provide higher-level modelling options, we introduce set variables and set constraints in local search by extending relevant local search concepts. We also propose a general scheme to follow in order to define what we call natural and balanced constraint measures, and accordingly define such measures for over a dozen set constraints. However, defining such measures for a new constraint is time-consuming and error-prone. To relieve the user from this, we provide generic measures for any set constraint modelled in monadic existential second-order logic. We also theoretically relate these measures to our proposed general scheme, and discuss implementation issues such as incremental algorithms and their worst-case complexities. To enable higher-level search algorithms, we introduce constraint-directed neighbourhoods in local search by proposing new constraint primitives for representing such neighbourhoods. Based on a constraint, possibly modelled in monadic existential second-order logic, these primitives return neighbourhoods with moves that are known in advance to achieve a decrease (or preservation, or increase) of the constraint measures, without the need to iterate over any other moves. We also present a framework for constraint-based local search where one can model and solve combinatorial problems with set variables and set constraints, use any set constraint modelled in monadic existential second-order logic, as well as use constraint-directed neighbourhoods. Experimental results on three real-life problems show the usefulness in practice of our theoretical results: our running times are comparable to the current state-of-the-art approaches to solving the considered problems.
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Marson-Pidgeon, Katrina Ann. "Seismogram synthesis for teleseismic events with application to source and structural studies." Phd thesis, 2001. http://hdl.handle.net/1885/47797.

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The aim of this thesis is to develop procedures for the modelling and inversion of teleseismic P and S waveforms which are as flexible as possible. This flexibility is necessary in order to obtain accurate source depth and mechanism estimates for small to moderate size events, such as those that are relevant in the context of monitoring the Comprehensive Nuclear-Test-Ban Treaty (CTBT). ¶ The main challenge for extending source depth and mechanism inversion methods to smaller events is to ensure that sufficiently accurate synthetic seismograms are available for comparison with observed records. An accurate phase-adaptive reflectivity method has therefore been developed, against which the performance of less computationally intensive approximations can be judged. The standard reflectivity method has been modified to allow for different crustal and upper mantle structures at the source and receiver, and the full effects of reverberations and conversions in these structures can be allowed for. Core reflections and refractions can also be included; these phases can become important at certain distance ranges. A slowness bundle approach has been developed, where a restricted slowness integration about the geometric slowness for the direct wave is undertaken at each frequency, allowing accurate results to be obtained whilst avoiding the expense of a full reflectivity technique. ¶ ...
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Mann, Rena Kaur. "Robust designs for field experiments with blocks." Thesis, 2011. http://hdl.handle.net/1828/3431.

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This thesis focuses on the design of field experiments with blocks to study treatment effects for a number of treatments. Small field plots are available but located in several blocks and each plot is assigned to a treatment in the experiment. Due to spatial correlation among the plots, the allocation of the treatments to plots has influence on the analysis of the treatment effects. When the spatial correlation is known, optimal allocations (designs) of the treatments to plots have been studied in the literature. However, the spatial correlation is usually unknown in practice, so we propose a robust criterion to study optimal designs of the treatments to plots. Neighbourhoods of correlation structures are introduced and a modified generalized least squares estimator is discussed. A simulated annealing algorithm is implemented to compute optimal/robust designs. Various results are obtained for different experimental settings. Some theoretical results are also proved in the thesis.
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Books on the topic "Neighbourhood algorithm"

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An exponential neighbourhood local search Algorithm for the single row facility location problem. Ahmedabad: Indian Institute of Management, 2011.

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Book chapters on the topic "Neighbourhood algorithm"

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Sambridge, M. S., and B. L. N. Kennett. "Seismic Event Location: Nonlinear Inversion Using a Neighbourhood Algorithm." In Monitoring the Comprehensive Nuclear-Test-Ban Treaty: Sourse Location, 241–57. Basel: Birkhäuser Basel, 2001. http://dx.doi.org/10.1007/978-3-0348-8250-7_15.

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Dahiya, Pankaj, Pankaj Mukhija, and Anmol Ratna Saxena. "Global Neighbourhood Algorithm Based Event-Triggered Automatic Generation Control." In Intelligent Computing Techniques for Smart Energy Systems, 683–92. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0214-9_71.

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Arajy, Yahya Z., Salwani Abdullah, and Saif Kifah. "Variable Neighbourhood Iterated Improvement Search Algorithm for Attribute Reduction Problems." In Lecture Notes in Computer Science, 554–68. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13563-2_47.

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Sevkli, Mehmet, and M. Emin Aydin. "A Variable Neighbourhood Search Algorithm for Job Shop Scheduling Problems." In Evolutionary Computation in Combinatorial Optimization, 261–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11730095_22.

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Jana, Sunanda, Anamika Dey, Arnab Kumar Maji, and Rajat Kumar Pal. "Solving Sudoku Using Neighbourhood-Based Mutation Approach of Genetic Algorithm." In Lecture Notes in Networks and Systems, 153–67. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-4287-6_11.

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Zhang, F., K. Qiu, and J. S. Kim. "Hyper-Star Graphs: Some Topological Properties and an Optimal Neighbourhood Broadcasting Algorithm." In Algorithms and Architectures for Parallel Processing, 526–34. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11197-1_40.

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Jančauskas, Vytautas. "Optimizing Neighbourhood Distances for a Variant of Fully-Informed Particle Swarm Algorithm." In Nature Inspired Cooperative Strategies for Optimization (NICSO 2013), 217–29. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-01692-4_17.

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Sun, Weitao, Jiwu Shu, and Weimin Zheng. "Deterministic Global Optimization with a Neighbourhood Determination Algorithm Based on Neural Networks." In Advances in Neural Networks — ISNN 2005, 700–705. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11427391_112.

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Martin-Smith, P., F. J. Pelayo, A. Diaz, J. Ortega, and A. Prieto. "A learning algorithm to obtain self-organizing maps using fixed neighbourhood Kohonen networks." In New Trends in Neural Computation, 297–304. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-56798-4_163.

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Lu, Zhigang, and Hong Shen. "A Fast Algorithm to Build New Users Similarity List in Neighbourhood-Based Collaborative Filtering." In Advances in Parallel and Distributed Computing and Ubiquitous Services, 229–36. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0068-3_30.

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Conference papers on the topic "Neighbourhood algorithm"

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Chen, Binhui, Rong Qu, Ruibin Bai, and Hisao Ishibuchi. "A Variable Neighbourhood Search Algorithm with Compound Neighbourhoods for VRPTW." In 5th International Conference on Operations Research and Enterprise Systems. SCITEPRESS - Science and Technology Publications, 2016. http://dx.doi.org/10.5220/0005661800250035.

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Tan*, Yuyang, Haijiang Zhang, and Chuan He. "Microseismic velocity model inversion using neighbourhood algorithm." In International Geophysical Conference, Qingdao, China, 17-20 April 2017. Society of Exploration Geophysicists and Chinese Petroleum Society, 2017. http://dx.doi.org/10.1190/igc2017-324.

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Singh, Geetanjali, Nirmala Sharma, and Harish Sharma. "Intelligent neighbourhood teaching learning based optimization algorithm." In 2017 International Conference on Computing, Communication and Automation (ICCCA). IEEE, 2017. http://dx.doi.org/10.1109/ccaa.2017.8229938.

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Jiang Guangyou and Kang Gewen. "A threshold segmentation algorithm based on neighbourhood characteristics." In Instruments (ICEMI). IEEE, 2011. http://dx.doi.org/10.1109/icemi.2011.6037917.

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Hartatik, Yahya Sugandi.Y, and Andri Syafrianto. "User Weighting Affect in Neighbourhood based Collaborative Filtering using Firefly Algorithm." In 2021 3rd International Conference on Electronics Representation and Algorithm (ICERA). IEEE, 2021. http://dx.doi.org/10.1109/icera53111.2021.9538665.

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Christie, M., G. Nicotra, M. Rotondi, and A. Godi. "Uncertainty Quantification in Producing Fields using the Neighbourhood Algorithm." In ECMOR X - 10th European Conference on the Mathematics of Oil Recovery. European Association of Geoscientists & Engineers, 2006. http://dx.doi.org/10.3997/2214-4609.201402501.

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Ding, Qiuqi, Haijun Song, Wenjian Geng, and Zongyuan Jiang. "Image Denoising Algorithm Using Neighbourhood Characteristics and Cycle Spinning." In 2011 Second International Conference on Digital Manufacturing and Automation (ICDMA). IEEE, 2011. http://dx.doi.org/10.1109/icdma.2011.153.

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Li, Lily D., Xinghuo Yu, Xiaodong Li, and William Guo. "A dynamic neighbourhood particle swarm optimisation algorithm for constrained optimisation." In IECON 2011 - 37th Annual Conference of IEEE Industrial Electronics. IEEE, 2011. http://dx.doi.org/10.1109/iecon.2011.6119795.

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Yang, Kunde, N. Chapman, and Yuanliang Ma. "Estimating parameter uncertainties in Geoacoustic inversion by a neighbourhood algorithm." In OCEANS 2006. IEEE, 2006. http://dx.doi.org/10.1109/oceans.2006.306799.

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Bisht, Kanchan, and Maroti Deshmukh. "Encryption algorithm based on knight’s tour and n-neighbourhood addition." In 2020 7th International Conference on Signal Processing and Integrated Networks (SPIN). IEEE, 2020. http://dx.doi.org/10.1109/spin48934.2020.9071013.

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