Is searching full text more effective than searching abstracts?
Directory of Open Access Journals (Sweden)
Lin Jimmy
2009-02-01
Full Text Available Abstract Background With the growing availability of full-text articles online, scientists and other consumers of the life sciences literature now have the ability to go beyond searching bibliographic records (title, abstract, metadata to directly access full-text content. Motivated by this emerging trend, I posed the following question: is searching full text more effective than searching abstracts? This question is answered by comparing text retrieval algorithms on MEDLINE® abstracts, full-text articles, and spans (paragraphs within full-text articles using data from the TREC 2007 genomics track evaluation. Two retrieval models are examined: bm25 and the ranking algorithm implemented in the open-source Lucene search engine. Results Experiments show that treating an entire article as an indexing unit does not consistently yield higher effectiveness compared to abstract-only search. However, retrieval based on spans, or paragraphs-sized segments of full-text articles, consistently outperforms abstract-only search. Results suggest that highest overall effectiveness may be achieved by combining evidence from spans and full articles. Conclusion Users searching full text are more likely to find relevant articles than searching only abstracts. This finding affirms the value of full text collections for text retrieval and provides a starting point for future work in exploring algorithms that take advantage of rapidly-growing digital archives. Experimental results also highlight the need to develop distributed text retrieval algorithms, since full-text articles are significantly longer than abstracts and may require the computational resources of multiple machines in a cluster. The MapReduce programming model provides a convenient framework for organizing such computations.
Is searching full text more effective than searching abstracts?
Lin, Jimmy
2009-02-03
With the growing availability of full-text articles online, scientists and other consumers of the life sciences literature now have the ability to go beyond searching bibliographic records (title, abstract, metadata) to directly access full-text content. Motivated by this emerging trend, I posed the following question: is searching full text more effective than searching abstracts? This question is answered by comparing text retrieval algorithms on MEDLINE abstracts, full-text articles, and spans (paragraphs) within full-text articles using data from the TREC 2007 genomics track evaluation. Two retrieval models are examined: bm25 and the ranking algorithm implemented in the open-source Lucene search engine. Experiments show that treating an entire article as an indexing unit does not consistently yield higher effectiveness compared to abstract-only search. However, retrieval based on spans, or paragraphs-sized segments of full-text articles, consistently outperforms abstract-only search. Results suggest that highest overall effectiveness may be achieved by combining evidence from spans and full articles. Users searching full text are more likely to find relevant articles than searching only abstracts. This finding affirms the value of full text collections for text retrieval and provides a starting point for future work in exploring algorithms that take advantage of rapidly-growing digital archives. Experimental results also highlight the need to develop distributed text retrieval algorithms, since full-text articles are significantly longer than abstracts and may require the computational resources of multiple machines in a cluster. The MapReduce programming model provides a convenient framework for organizing such computations.
NASA Taxonomies for Searching Problem Reports and FMEAs
Malin, Jane T.; Throop, David R.
2006-01-01
Many types of hazard and risk analyses are used during the life cycle of complex systems, including Failure Modes and Effects Analysis (FMEA), Hazard Analysis, Fault Tree and Event Tree Analysis, Probabilistic Risk Assessment, Reliability Analysis and analysis of Problem Reporting and Corrective Action (PRACA) databases. The success of these methods depends on the availability of input data and the analysts knowledge. Standard nomenclature can increase the reusability of hazard, risk and problem data. When nomenclature in the source texts is not standard, taxonomies with mapping words (sets of rough synonyms) can be combined with semantic search to identify items and tag them with metadata based on a rich standard nomenclature. Semantic search uses word meanings in the context of parsed phrases to find matches. The NASA taxonomies provide the word meanings. Spacecraft taxonomies and ontologies (generalization hierarchies with attributes and relationships, based on terms meanings) are being developed for types of subsystems, functions, entities, hazards and failures. The ontologies are broad and general, covering hardware, software and human systems. Semantic search of Space Station texts was used to validate and extend the taxonomies. The taxonomies have also been used to extract system connectivity (interaction) models and functions from requirements text. Now the Reconciler semantic search tool and the taxonomies are being applied to improve search in the Space Shuttle PRACA database, to discover recurring patterns of failure. Usual methods of string search and keyword search fall short because the entries are terse and have numerous shortcuts (irregular abbreviations, nonstandard acronyms, cryptic codes) and modifier words cannot be used in sentence context to refine the search. The limited and fixed FMEA categories associated with the entries do not make the fine distinctions needed in the search. The approach assigns PRACA report titles to problem classes in
The Weaknesses of Full-Text Searching
Beall, Jeffrey
2008-01-01
This paper provides a theoretical critique of the deficiencies of full-text searching in academic library databases. Because full-text searching relies on matching words in a search query with words in online resources, it is an inefficient method of finding information in a database. This matching fails to retrieve synonyms, and it also retrieves…
Chemical-text hybrid search engines.
Zhou, Yingyao; Zhou, Bin; Jiang, Shumei; King, Frederick J
2010-01-01
As the amount of chemical literature increases, it is critical that researchers be enabled to accurately locate documents related to a particular aspect of a given compound. Existing solutions, based on text and chemical search engines alone, suffer from the inclusion of "false negative" and "false positive" results, and cannot accommodate diverse repertoire of formats currently available for chemical documents. To address these concerns, we developed an approach called Entity-Canonical Keyword Indexing (ECKI), which converts a chemical entity embedded in a data source into its canonical keyword representation prior to being indexed by text search engines. We implemented ECKI using Microsoft Office SharePoint Server Search, and the resultant hybrid search engine not only supported complex mixed chemical and keyword queries but also was applied to both intranet and Internet environments. We envision that the adoption of ECKI will empower researchers to pose more complex search questions that were not readily attainable previously and to obtain answers at much improved speed and accuracy.
Searching Harvard Business Review Online. . . Lessons in Searching a Full Text Database.
Tenopir, Carol
1985-01-01
This article examines the Harvard Business Review Online (HBRO) database (bibliographic description fields, abstracts, extracted information, full text, subject descriptors) and reports on 31 sample HBRO searches conducted in Bibliographic Retrieval Services to test differences between searching full text and searching bibliographic record. Sample…
Gaussian variable neighborhood search for the file transfer scheduling problem
Directory of Open Access Journals (Sweden)
Dražić Zorica
2016-01-01
Full Text Available This paper presents new modifications of Variable Neighborhood Search approach for solving the file transfer scheduling problem. To obtain better solutions in a small neighborhood of a current solution, we implement two new local search procedures. As Gaussian Variable Neighborhood Search showed promising results when solving continuous optimization problems, its implementation in solving the discrete file transfer scheduling problem is also presented. In order to apply this continuous optimization method to solve the discrete problem, mapping of uncountable set of feasible solutions into a finite set is performed. Both local search modifications gave better results for the large size instances, as well as better average performance for medium and large size instances. One local search modification achieved significant acceleration of the algorithm. The numerical experiments showed that the results obtained by Gaussian modifications are comparable with the results obtained by standard VNS based algorithms, developed for combinatorial optimization. In some cases Gaussian modifications gave even better results. [Projekat Ministarstava nauke Republike Srbije, br. 174010
A Local Search Modeling for Constrained Optimum Paths Problems (Extended Abstract
Directory of Open Access Journals (Sweden)
Quang Dung Pham
2009-10-01
Full Text Available Constrained Optimum Path (COP problems appear in many real-life applications, especially on communication networks. Some of these problems have been considered and solved by specific techniques which are usually difficult to extend. In this paper, we introduce a novel local search modeling for solving some COPs by local search. The modeling features the compositionality, modularity, reuse and strengthens the benefits of Constrained-Based Local Search. We also apply the modeling to the edge-disjoint paths problem (EDP. We show that side constraints can easily be added in the model. Computational results show the significance of the approach.
Solving k-Barrier Coverage Problem Using Modified Gravitational Search Algorithm
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Yanhua Zhang
2017-01-01
Full Text Available Coverage problem is a critical issue in wireless sensor networks for security applications. The k-barrier coverage is an effective measure to ensure robustness. In this paper, we formulate the k-barrier coverage problem as a constrained optimization problem and introduce the energy constraint of sensor node to prolong the lifetime of the k-barrier coverage. A novel hybrid particle swarm optimization and gravitational search algorithm (PGSA is proposed to solve this problem. The proposed PGSA adopts a k-barrier coverage generation strategy based on probability and integrates the exploitation ability in particle swarm optimization to update the velocity and enhance the global search capability and introduce the boundary mutation strategy of an agent to increase the population diversity and search accuracy. Extensive simulations are conducted to demonstrate the effectiveness of our proposed algorithm.
Full text and figure display improves bioscience literature search.
Directory of Open Access Journals (Sweden)
Anna Divoli
Full Text Available When reading bioscience journal articles, many researchers focus attention on the figures and their captions. This observation led to the development of the BioText literature search engine, a freely available Web-based application that allows biologists to search over the contents of Open Access Journals, and see figures from the articles displayed directly in the search results. This article presents a qualitative assessment of this system in the form of a usability study with 20 biologist participants using and commenting on the system. 19 out of 20 participants expressed a desire to use a bioscience literature search engine that displays articles' figures alongside the full text search results. 15 out of 20 participants said they would use a caption search and figure display interface either frequently or sometimes, while 4 said rarely and 1 said undecided. 10 out of 20 participants said they would use a tool for searching the text of tables and their captions either frequently or sometimes, while 7 said they would use it rarely if at all, 2 said they would never use it, and 1 was undecided. This study found evidence, supporting results of an earlier study, that bioscience literature search systems such as PubMed should show figures from articles alongside search results. It also found evidence that full text and captions should be searched along with the article title, metadata, and abstract. Finally, for a subset of users and information needs, allowing for explicit search within captions for figures and tables is a useful function, but it is not entirely clear how to cleanly integrate this within a more general literature search interface. Such a facility supports Open Access publishing efforts, as it requires access to full text of documents and the lifting of restrictions in order to show figures in the search interface.
A DE-Based Scatter Search for Global Optimization Problems
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Kun Li
2015-01-01
Full Text Available This paper proposes a hybrid scatter search (SS algorithm for continuous global optimization problems by incorporating the evolution mechanism of differential evolution (DE into the reference set updated procedure of SS to act as the new solution generation method. This hybrid algorithm is called a DE-based SS (SSDE algorithm. Since different kinds of mutation operators of DE have been proposed in the literature and they have shown different search abilities for different kinds of problems, four traditional mutation operators are adopted in the hybrid SSDE algorithm. To adaptively select the mutation operator that is most appropriate to the current problem, an adaptive mechanism for the candidate mutation operators is developed. In addition, to enhance the exploration ability of SSDE, a reinitialization method is adopted to create a new population and subsequently construct a new reference set whenever the search process of SSDE is trapped in local optimum. Computational experiments on benchmark problems show that the proposed SSDE is competitive or superior to some state-of-the-art algorithms in the literature.
A "feasible direction" search for Lineal Programming problem solving
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Jaime U Malpica Angarita
2003-07-01
Full Text Available The study presents an approach to solve linear programming problems with no artificial variables. A primal linear minimization problem is standard form and its associated dual linear maximization problem are used. Initially, the dual (or a partial dual program is solved by a "feasible direction" search, where the Karush-Kuhn-Tucker conditions help to verify its optimality and then its feasibility. The "feasible direction" search exploits the characteristics of the convex polyhedron (or prototype formed by the dual program constraints to find a starting point and then follows line segments, whose directions are found in afine subspaces defined by boundary hyperplanes of polyhedral faces, to find next points up to the (an optimal one. Them, the remaining dual constraints not satisfaced at that optimal dual point, if there are any, are handled as nonbasic variables of the primal program, which is to be solved by such "feasible direction" search.
Adiabatic quantum search algorithm for structured problems
International Nuclear Information System (INIS)
Roland, Jeremie; Cerf, Nicolas J.
2003-01-01
The study of quantum computation has been motivated by the hope of finding efficient quantum algorithms for solving classically hard problems. In this context, quantum algorithms by local adiabatic evolution have been shown to solve an unstructured search problem with a quadratic speedup over a classical search, just as Grover's algorithm. In this paper, we study how the structure of the search problem may be exploited to further improve the efficiency of these quantum adiabatic algorithms. We show that by nesting a partial search over a reduced set of variables into a global search, it is possible to devise quantum adiabatic algorithms with a complexity that, although still exponential, grows with a reduced order in the problem size
Full text and figure display improves bioscience literature search.
Divoli, Anna; Wooldridge, Michael A; Hearst, Marti A
2010-04-14
When reading bioscience journal articles, many researchers focus attention on the figures and their captions. This observation led to the development of the BioText literature search engine, a freely available Web-based application that allows biologists to search over the contents of Open Access Journals, and see figures from the articles displayed directly in the search results. This article presents a qualitative assessment of this system in the form of a usability study with 20 biologist participants using and commenting on the system. 19 out of 20 participants expressed a desire to use a bioscience literature search engine that displays articles' figures alongside the full text search results. 15 out of 20 participants said they would use a caption search and figure display interface either frequently or sometimes, while 4 said rarely and 1 said undecided. 10 out of 20 participants said they would use a tool for searching the text of tables and their captions either frequently or sometimes, while 7 said they would use it rarely if at all, 2 said they would never use it, and 1 was undecided. This study found evidence, supporting results of an earlier study, that bioscience literature search systems such as PubMed should show figures from articles alongside search results. It also found evidence that full text and captions should be searched along with the article title, metadata, and abstract. Finally, for a subset of users and information needs, allowing for explicit search within captions for figures and tables is a useful function, but it is not entirely clear how to cleanly integrate this within a more general literature search interface. Such a facility supports Open Access publishing efforts, as it requires access to full text of documents and the lifting of restrictions in order to show figures in the search interface.
da Luz, Marcos G. E.; Grosberg, Alexander; Raposo, Ernesto P.; Viswanathan, Gandhi M.
2009-10-01
`I can't find my keys!' Who hasn't gone through this experience when leaving, in a hurry, to attend to some urgent matter? The keys could be in many different places. Unless one remembers where he or she has left the keys, the only solution is to look around, more or less randomly. Random searches are common because in many cases the locations of the specific targets are not known a priori. Indeed, such problems have been discussed in diverse contexts, attracting the interest of scientists from many fields, for example: the dynamical or stochastic search for a stable minimum in a complex energy landscape, relevant to systems such as glasses, protein (folding), and others; oil recovery from mature reservoirs; proteins searching for their specific target sites on DNA; animal foraging; survival at the edge of extinction due to low availability of energetic resources; automated searches of registers in high-capacity databases, search engine (e.g., `crawlers') that explore the internet; and even pizza delivery in a jammed traffic system of a medium-size town. In this way, the subject is interesting, challenging and has recently become an important scientific area of investigation. Although the applications are diverse, the underlying physical mechanisms are the same which will become clear in this special issue. Moreover, the inherent complexity of the problem, the abundance of ideas and methods found in this growing interdisciplinary field of research is studied in many areas of physics. In particular, the concepts and methods of statistical mechanics are particularly useful to the study of random searches. On one hand, it centres on how to find the global or local maxima of search efficiency functions with incomplete information. This is, of course, related to the long tradition in physics of using different conceptual and mathematical tools, such as variational methods, to extremize relevant quantities, e.g., energy, entropy and action. Such ideas and approaches are
Complex Sequencing Problems and Local Search Heuristics
Brucker, P.; Hurink, Johann L.; Osman, I.H.; Kelly, J.P.
1996-01-01
Many problems can be formulated as complex sequencing problems. We will present problems in flexible manufacturing that have such a formulation and apply local search methods like iterative improvement, simulated annealing and tabu search to solve these problems. Computational results are reported.
Expected Fitness Gains of Randomized Search Heuristics for the Traveling Salesperson Problem.
Nallaperuma, Samadhi; Neumann, Frank; Sudholt, Dirk
2017-01-01
Randomized search heuristics are frequently applied to NP-hard combinatorial optimization problems. The runtime analysis of randomized search heuristics has contributed tremendously to our theoretical understanding. Recently, randomized search heuristics have been examined regarding their achievable progress within a fixed-time budget. We follow this approach and present a fixed-budget analysis for an NP-hard combinatorial optimization problem. We consider the well-known Traveling Salesperson Problem (TSP) and analyze the fitness increase that randomized search heuristics are able to achieve within a given fixed-time budget. In particular, we analyze Manhattan and Euclidean TSP instances and Randomized Local Search (RLS), (1+1) EA and (1+[Formula: see text]) EA algorithms for the TSP in a smoothed complexity setting, and derive the lower bounds of the expected fitness gain for a specified number of generations.
Pervez, Zeeshan; Ahmad, Mahmood; Khattak, Asad Masood; Ramzan, Naeem; Khan, Wajahat Ali
2017-01-01
Public cloud storage services are becoming prevalent and myriad data sharing, archiving and collaborative services have emerged which harness the pay-as-you-go business model of public cloud. To ensure privacy and confidentiality often encrypted data is outsourced to such services, which further complicates the process of accessing relevant data by using search queries. Search over encrypted data schemes solve this problem by exploiting cryptographic primitives and secure indexing to identify outsourced data that satisfy the search criteria. Almost all of these schemes rely on exact matching between the encrypted data and search criteria. A few schemes which extend the notion of exact matching to similarity based search, lack realism as those schemes rely on trusted third parties or due to increase storage and computational complexity. In this paper we propose Oblivious Similarity based Search ([Formula: see text]) for encrypted data. It enables authorized users to model their own encrypted search queries which are resilient to typographical errors. Unlike conventional methodologies, [Formula: see text] ranks the search results by using similarity measure offering a better search experience than exact matching. It utilizes encrypted bloom filter and probabilistic homomorphic encryption to enable authorized users to access relevant data without revealing results of search query evaluation process to the untrusted cloud service provider. Encrypted bloom filter based search enables [Formula: see text] to reduce search space to potentially relevant encrypted data avoiding unnecessary computation on public cloud. The efficacy of [Formula: see text] is evaluated on Google App Engine for various bloom filter lengths on different cloud configurations.
Search across Different Media: Numeric Data Sets and Text Files
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Michael Buckland
2006-12-01
Full Text Available Digital technology encourages the hope of searching across and between different media forms (text, sound, image, numeric data. Topic searches are described in two different media: text files and socioeconomic numeric databases and also for transverse searching, whereby retrieved text is used to find topically related numeric data and vice versa. Direct transverse searching across different media is impossible. Descriptive metadata provide enabling infrastructure, but usually require mappings between different vocabularies and a search-term recommender system. Statistical association techniques and natural-language processing can help. Searches in socioeconomic numeric databases ordinarily require that place and time be specified.
Global Search Strategies for Solving Multilinear Least-Squares Problems
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Mats Andersson
2012-04-01
Full Text Available The multilinear least-squares (MLLS problem is an extension of the linear least-squares problem. The difference is that a multilinear operator is used in place of a matrix-vector product. The MLLS is typically a large-scale problem characterized by a large number of local minimizers. It originates, for instance, from the design of filter networks. We present a global search strategy that allows for moving from one local minimizer to a better one. The efficiency of this strategy is illustrated by the results of numerical experiments performed for some problems related to the design of filter networks.
SERVICES OF FULL-TEXT SEARCHING IN A DISTRIBUTED INFORMATION ENVIRONMENT (PROJECT HUMANITARIANA
Directory of Open Access Journals (Sweden)
S. K. Lyapin
2015-01-01
Full Text Available Problem statement. We justify the possibility of full-text search services application in both universal and specialized (in terms of resource base digital libraries for the extraction and analysis of the context knowledge in the humanities. The architecture and services of virtual information and resource center for extracting knowledge from the humanitarian texts generated by «Humanitariana» project are described. The functional integration of the resources and services for a full-text search in a distributed decentralized environment, organized in the Internet / Intranet architecture under the control of the client (user browser accessing a variety of independent servers. An algorithm for a distributed full-text query implementation is described. Methods. Method of combining requency-ranked and paragraph-oriented full-text queries is used: the first are used for the preliminary analysis of the subject area or a combination product (explication of "vertical" context, or macro context, the second - for the explication of "horizontal" context, or micro context within copyright paragraph. The results of the frequency-ranked queries are used to compile paragraph-oriented queries. Results. The results of textual research are shown on the topics "The question of fact in Russian philosophy", "The question of loneliness in Russian philosophy and culture". About 50 pieces of context knowledge on the total resource base of about 2,500 full-text resources have been explicated and briefly described to their further expert investigating. Practical significance. The proposed technology (advanced full-text searching services in a distributed information environment can be used for the information support of humanitarian studies and education in the humanities, for functional integration of resources and services of various organizations, for carrying out interdisciplinary research.
A hybrid guided neighborhood search for the disjunctively constrained knapsack problem
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Mhand Hifi
2015-12-01
Full Text Available In this paper, we investigate the use of a hybrid guided neighborhood search for solving the disjunctively constrained knapsack problem. The studied problem may be viewed as a combination of two NP-hard combinatorial optimization problems: the weighted-independent set and the classical binary knapsack. The proposed algorithm is a hybrid approach that combines both deterministic and random local searches. The deterministic local search is based on a descent method, where both building and exploring procedures are alternatively used for improving the solution at hand. In order to escape from a local optima, a random local search strategy is introduced which is based on a modified ant colony optimization system. During the search process, the ant colony optimization system tries to diversify and to enhance the solutions using some informations collected from the previous iterations. Finally, the proposed algorithm is computationally analyzed on a set of benchmark instances available in the literature. The provided results are compared to those realized by both the Cplex solver and a recent algorithm of the literature. The computational part shows that the obtained results improve most existing solution values.
Wolf Search Algorithm for Solving Optimal Reactive Power Dispatch Problem
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Kanagasabai Lenin
2015-03-01
Full Text Available This paper presents a new bio-inspired heuristic optimization algorithm called the Wolf Search Algorithm (WSA for solving the multi-objective reactive power dispatch problem. Wolf Search algorithm is a new bio – inspired heuristic algorithm which based on wolf preying behaviour. The way wolves search for food and survive by avoiding their enemies has been imitated to formulate the algorithm for solving the reactive power dispatches. And the speciality of wolf is possessing both individual local searching ability and autonomous flocking movement and this special property has been utilized to formulate the search algorithm .The proposed (WSA algorithm has been tested on standard IEEE 30 bus test system and simulation results shows clearly about the good performance of the proposed algorithm .
Solving Large Clustering Problems with Meta-Heuristic Search
DEFF Research Database (Denmark)
Turkensteen, Marcel; Andersen, Kim Allan; Bang-Jensen, Jørgen
In Clustering Problems, groups of similar subjects are to be retrieved from data sets. In this paper, Clustering Problems with the frequently used Minimum Sum-of-Squares Criterion are solved using meta-heuristic search. Tabu search has proved to be a successful methodology for solving optimization...... problems, but applications to large clustering problems are rare. The simulated annealing heuristic has mainly been applied to relatively small instances. In this paper, we implement tabu search and simulated annealing approaches and compare them to the commonly used k-means approach. We find that the meta-heuristic...
ONTOLOGY OF COMPUTATIONAL EXPERIMENT ORGANIZATION IN PROBLEMS OF SEARCHING AND SORTING
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A. Spivakovsky
2011-05-01
Full Text Available Ontologies are a key technology of semantic processing of knowledge. We examine a methodology of ontology’s usage for the organization of computational experiment in problems of searching and sorting in studies of the course "Basics of algorithms and programming".
Directory of Open Access Journals (Sweden)
A. K. M. Foysal Ahmed
2018-03-01
Full Text Available The classical capacitated vehicle routing problem (CVRP is a very popular combinatorial optimization problem in the field of logistics and supply chain management. Although CVRP has drawn interests of many researchers, no standard way has been established yet to obtain best known solutions for all the different problem sets. We propose an efficient algorithm Bilayer Local Search-based Particle Swarm Optimization (BLS-PSO along with a novel decoding method to solve CVRP. Decoding method is important to relate the encoded particle position to a feasible CVRP solution. In bilayer local search, one layer of local search is for the whole population in any iteration whereas another one is applied only on the pool of the best particles generated in different generations. Such searching strategies help the BLS-PSO to perform better than the existing proposals by obtaining best known solutions for most of the existing benchmark problems within very reasonable computational time. Computational results also show that the performance achieved by the proposed algorithm outperforms other PSO-based approaches.
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Jürgen eSchmidhuber
2013-06-01
Full Text Available Most of computer science focuses on automatically solving given computational problems. I focus on automatically inventing or discovering problems in a way inspired by the playful behavior of animals and humans, to train a more and more general problem solver from scratch in an unsupervised fashion. Consider the infinite set of all computable descriptions of tasks with possibly computable solutions. The novel algorithmic framework POWERPLAY (2011 continually searches the space of possible pairs of new tasks and modifications of the current problem solver, until it finds a more powerful problem solver that provably solves all previously learned tasks plus the new one, while the unmodified predecessor does not. Wow-effects are achieved by continually making previously learned skills more efficient such that they require less time and space. New skills may (partially re-use previously learned skills. POWERPLAY's search orders candidate pairs of tasks and solver modifications by their conditional computational (time & space complexity, given the stored experience so far. The new task and its corresponding task-solving skill are those first found and validated. The computational costs of validating new tasks need not grow with task repertoire size. POWERPLAY's ongoing search for novelty keeps breaking the generalization abilities of its present solver. This is related to Goedel's sequence of increasingly powerful formal theories based on adding formerly unprovable statements to the axioms without affecting previously provable theorems. The continually increasing repertoire of problem solving procedures can be exploited by a parallel search for solutions to additional externally posed tasks. POWERPLAY may be viewed as a greedy but practical implementation of basic principles of creativity. A first experimental analysis can be found in separate papers [58, 56, 57].
Searching for Significance in Unstructured Data: Text Mining with Leximancer
Thomas, David A.
2014-01-01
Scholars in many knowledge domains rely on sophisticated information technologies to search for and retrieve records and publications pertinent to their research interests. But what is a scholar to do when a search identifies hundreds of documents, any of which might be vital or irrelevant to his or her work? The problem is further complicated by…
A GPU Implementation of Local Search Operators for Symmetric Travelling Salesman Problem
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Juraj Fosin
2013-06-01
Full Text Available The Travelling Salesman Problem (TSP is one of the most studied combinatorial optimization problem which is significant in many practical applications in transportation problems. The TSP problem is NP-hard problem and requires large computation power to be solved by the exact algorithms. In the past few years, fast development of general-purpose Graphics Processing Units (GPUs has brought huge improvement in decreasing the applications’ execution time. In this paper, we implement 2-opt and 3-opt local search operators for solving the TSP on the GPU using CUDA. The novelty presented in this paper is a new parallel iterated local search approach with 2-opt and 3-opt operators for symmetric TSP, optimized for the execution on GPUs. With our implementation large TSP problems (up to 85,900 cities can be solved using the GPU. We will show that our GPU implementation can be up to 20x faster without losing quality for all TSPlib problems as well as for our CRO TSP problem.
Advice Complexity of the Online Search Problem
DEFF Research Database (Denmark)
Clemente, Jhoirene; Hromkovič, Juraj; Komm, Dennis
2016-01-01
the minimum amount of information needed in order to achieve a certain competitive ratio. We design an algorithm that reads $b$ bits of advice and achieves a competitive ratio of (M/m)^{1/(2^b+1)} where M and m are the maximum and minimum price in the input. We also give a matching lower bound. Furthermore......The online search problem is a fundamental problem in finance. The numerous direct applications include searching for optimal prices for commodity trading and trading foreign currencies. In this paper, we analyze the advice complexity of this problem. In particular, we are interested in identifying......, we compare the power of advice and randomization for this problem....
Online Information Search Performance and Search Strategies in a Health Problem-Solving Scenario.
Sharit, Joseph; Taha, Jessica; Berkowsky, Ronald W; Profita, Halley; Czaja, Sara J
2015-01-01
Although access to Internet health information can be beneficial, solving complex health-related problems online is challenging for many individuals. In this study, we investigated the performance of a sample of 60 adults ages 18 to 85 years in using the Internet to resolve a relatively complex health information problem. The impact of age, Internet experience, and cognitive abilities on measures of search time, amount of search, and search accuracy was examined, and a model of Internet information seeking was developed to guide the characterization of participants' search strategies. Internet experience was found to have no impact on performance measures. Older participants exhibited longer search times and lower amounts of search but similar search accuracy performance as their younger counterparts. Overall, greater search accuracy was related to an increased amount of search but not to increased search duration and was primarily attributable to higher cognitive abilities, such as processing speed, reasoning ability, and executive function. There was a tendency for those who were younger, had greater Internet experience, and had higher cognitive abilities to use a bottom-up (i.e., analytic) search strategy, although use of a top-down (i.e., browsing) strategy was not necessarily unsuccessful. Implications of the findings for future studies and design interventions are discussed.
Directory of Open Access Journals (Sweden)
Sunxin Wang
2014-01-01
Full Text Available This paper presents a combination of variable neighbourhood search and mathematical programming to minimize the sum of earliness and tardiness penalty costs of all operations for just-in-time job-shop scheduling problem (JITJSSP. Unlike classical E/T scheduling problem with each job having its earliness or tardiness penalty cost, each operation in this paper has its earliness and tardiness penalties, which are paid if the operation is completed before or after its due date. Our hybrid algorithm combines (i a variable neighbourhood search procedure to explore the huge feasible solution spaces efficiently by alternating the swap and insertion neighbourhood structures and (ii a mathematical programming model to optimize the completion times of the operations for a given solution in each iteration procedure. Additionally, a threshold accepting mechanism is proposed to diversify the local search of variable neighbourhood search. Computational results on the 72 benchmark instances show that our algorithm can obtain the best known solution for 40 problems, and the best known solutions for 33 problems are updated.
Impact of Glaucoma and Dry Eye on Text-Based Searching
Sun, Michelle J.; Rubin, Gary S.; Akpek, Esen K.; Ramulu, Pradeep Y.
2017-01-01
Purpose We determine if visual field loss from glaucoma and/or measures of dry eye severity are associated with difficulty searching, as judged by slower search times on a text-based search task. Methods Glaucoma patients with bilateral visual field (VF) loss, patients with clinically significant dry eye, and normally-sighted controls were enrolled from the Wilmer Eye Institute clinics. Subjects searched three Yellow Pages excerpts for a specific phone number, and search time was recorded. Results A total of 50 glaucoma subjects, 40 dry eye subjects, and 45 controls completed study procedures. On average, glaucoma patients exhibited 57% longer search times compared to controls (95% confidence interval [CI], 26%–96%, P Dry eye subjects demonstrated similar search times compared to controls, though worse Ocular Surface Disease Index (OSDI) vision-related subscores were associated with longer search times (P dry eye (P > 0.08 for Schirmer's testing without anesthesia, corneal fluorescein staining, and tear film breakup time). Conclusions Text-based visual search is slower for glaucoma patients with greater levels of VF loss and dry eye patients with greater self-reported visual difficulty, and these difficulties may contribute to decreased quality of life in these groups. Translational Relevance Visual search is impaired in glaucoma and dry eye groups compared to controls, highlighting the need for compensatory strategies and tools to assist individuals in overcoming their deficiencies. PMID:28670502
Augmenting Oracle Text with the UMLS for enhanced searching of free-text medical reports.
Ding, Jing; Erdal, Selnur; Dhaval, Rakesh; Kamal, Jyoti
2007-10-11
The intrinsic complexity of free-text medical reports imposes great challenges for information retrieval systems. We have developed a prototype search engine for retrieving clinical reports that leverages the powerful indexing and querying capabilities of Oracle Text, and the rich biomedical domain knowledge and semantic structures that are captured in the UMLS Metathesaurus.
An Elite Decision Making Harmony Search Algorithm for Optimization Problem
Directory of Open Access Journals (Sweden)
Lipu Zhang
2012-01-01
Full Text Available This paper describes a new variant of harmony search algorithm which is inspired by a well-known item “elite decision making.” In the new algorithm, the good information captured in the current global best and the second best solutions can be well utilized to generate new solutions, following some probability rule. The generated new solution vector replaces the worst solution in the solution set, only if its fitness is better than that of the worst solution. The generating and updating steps and repeated until the near-optimal solution vector is obtained. Extensive computational comparisons are carried out by employing various standard benchmark optimization problems, including continuous design variables and integer variables minimization problems from the literature. The computational results show that the proposed new algorithm is competitive in finding solutions with the state-of-the-art harmony search variants.
An Improved Crow Search Algorithm Applied to Energy Problems
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Primitivo Díaz
2018-03-01
Full Text Available The efficient use of energy in electrical systems has become a relevant topic due to its environmental impact. Parameter identification in induction motors and capacitor allocation in distribution networks are two representative problems that have strong implications in the massive use of energy. From an optimization perspective, both problems are considered extremely complex due to their non-linearity, discontinuity, and high multi-modality. These characteristics make difficult to solve them by using standard optimization techniques. On the other hand, metaheuristic methods have been widely used as alternative optimization algorithms to solve complex engineering problems. The Crow Search Algorithm (CSA is a recent metaheuristic method based on the intelligent group behavior of crows. Although CSA presents interesting characteristics, its search strategy presents great difficulties when it faces high multi-modal formulations. In this paper, an improved version of the CSA method is presented to solve complex optimization problems of energy. In the new algorithm, two features of the original CSA are modified: (I the awareness probability (AP and (II the random perturbation. With such adaptations, the new approach preserves solution diversity and improves the convergence to difficult high multi-modal optima. In order to evaluate its performance, the proposed algorithm has been tested in a set of four optimization problems which involve induction motors and distribution networks. The results demonstrate the high performance of the proposed method when it is compared with other popular approaches.
A Hybrid Differential Evolution and Tree Search Algorithm for the Job Shop Scheduling Problem
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Rui Zhang
2011-01-01
Full Text Available The job shop scheduling problem (JSSP is a notoriously difficult problem in combinatorial optimization. In terms of the objective function, most existing research has been focused on the makespan criterion. However, in contemporary manufacturing systems, due-date-related performances are more important because they are essential for maintaining a high service reputation. Therefore, in this study we aim at minimizing the total weighted tardiness in JSSP. Considering the high complexity, a hybrid differential evolution (DE algorithm is proposed for the problem. To enhance the overall search efficiency, a neighborhood property of the problem is discovered, and then a tree search procedure is designed and embedded into the DE framework. According to the extensive computational experiments, the proposed approach is efficient in solving the job shop scheduling problem with total weighted tardiness objective.
Improving e-book access via a library-developed full-text search tool.
Foust, Jill E; Bergen, Phillip; Maxeiner, Gretchen L; Pawlowski, Peter N
2007-01-01
This paper reports on the development of a tool for searching the contents of licensed full-text electronic book (e-book) collections. The Health Sciences Library System (HSLS) provides services to the University of Pittsburgh's medical programs and large academic health system. The HSLS has developed an innovative tool for federated searching of its e-book collections. Built using the XML-based Vivísimo development environment, the tool enables a user to perform a full-text search of over 2,500 titles from the library's seven most highly used e-book collections. From a single "Google-style" query, results are returned as an integrated set of links pointing directly to relevant sections of the full text. Results are also grouped into categories that enable more precise retrieval without reformulation of the search. A heuristic evaluation demonstrated the usability of the tool and a web server log analysis indicated an acceptable level of usage. Based on its success, there are plans to increase the number of online book collections searched. This library's first foray into federated searching has produced an effective tool for searching across large collections of full-text e-books and has provided a good foundation for the development of other library-based federated searching products.
Evaluating Open-Source Full-Text Search Engines for Matching ICD-10 Codes.
Jurcău, Daniel-Alexandru; Stoicu-Tivadar, Vasile
2016-01-01
This research presents the results of evaluating multiple free, open-source engines on matching ICD-10 diagnostic codes via full-text searches. The study investigates what it takes to get an accurate match when searching for a specific diagnostic code. For each code the evaluation starts by extracting the words that make up its text and continues with building full-text search queries from the combinations of these words. The queries are then run against all the ICD-10 codes until a match indicates the code in question as a match with the highest relative score. This method identifies the minimum number of words that must be provided in order for the search engines choose the desired entry. The engines analyzed include a popular Java-based full-text search engine, a lightweight engine written in JavaScript which can even execute on the user's browser, and two popular open-source relational database management systems.
Improving e-book access via a library-developed full-text search tool*
Foust, Jill E.; Bergen, Phillip; Maxeiner, Gretchen L.; Pawlowski, Peter N.
2007-01-01
Purpose: This paper reports on the development of a tool for searching the contents of licensed full-text electronic book (e-book) collections. Setting: The Health Sciences Library System (HSLS) provides services to the University of Pittsburgh's medical programs and large academic health system. Brief Description: The HSLS has developed an innovative tool for federated searching of its e-book collections. Built using the XML-based Vivísimo development environment, the tool enables a user to perform a full-text search of over 2,500 titles from the library's seven most highly used e-book collections. From a single “Google-style” query, results are returned as an integrated set of links pointing directly to relevant sections of the full text. Results are also grouped into categories that enable more precise retrieval without reformulation of the search. Results/Evaluation: A heuristic evaluation demonstrated the usability of the tool and a web server log analysis indicated an acceptable level of usage. Based on its success, there are plans to increase the number of online book collections searched. Conclusion: This library's first foray into federated searching has produced an effective tool for searching across large collections of full-text e-books and has provided a good foundation for the development of other library-based federated searching products. PMID:17252065
Directory of Open Access Journals (Sweden)
Suk Ho Jin
2017-06-01
Full Text Available The nurse rostering problem is an important search problem that features many constraints. In a nurse rostering problem, these constraints are defined by processes such as maintaining work regulations, assigning nurse shifts, and considering nurse preferences. A number of approaches to address these constraints, such as penalty function methods, have been investigated in the literature. We propose two types of hybrid metaheuristic approaches for solving the nurse rostering problem, which are based on combining harmony search techniques and artificial immune systems to balance local and global searches and prevent slow convergence speeds and prematurity. The proposed algorithms are evaluated against a benchmarking dataset of nurse rostering problems; the results show that they identify better or best known solutions compared to those identified in other studies for most instances. The results also show that the combination of harmony search and artificial immune systems is better suited than using single metaheuristic or other hybridization methods for finding upper-bound solutions for nurse rostering problems and discrete optimization problems.
Variable Neighborhood Search for Parallel Machines Scheduling Problem with Step Deteriorating Jobs
Directory of Open Access Journals (Sweden)
Wenming Cheng
2012-01-01
Full Text Available In many real scheduling environments, a job processed later needs longer time than the same job when it starts earlier. This phenomenon is known as scheduling with deteriorating jobs to many industrial applications. In this paper, we study a scheduling problem of minimizing the total completion time on identical parallel machines where the processing time of a job is a step function of its starting time and a deteriorating date that is individual to all jobs. Firstly, a mixed integer programming model is presented for the problem. And then, a modified weight-combination search algorithm and a variable neighborhood search are employed to yield optimal or near-optimal schedule. To evaluate the performance of the proposed algorithms, computational experiments are performed on randomly generated test instances. Finally, computational results show that the proposed approaches obtain near-optimal solutions in a reasonable computational time even for large-sized problems.
Test-state approach to the quantum search problem
International Nuclear Information System (INIS)
Sehrawat, Arun; Nguyen, Le Huy; Englert, Berthold-Georg
2011-01-01
The search for 'a quantum needle in a quantum haystack' is a metaphor for the problem of finding out which one of a permissible set of unitary mappings - the oracles - is implemented by a given black box. Grover's algorithm solves this problem with quadratic speedup as compared with the analogous search for 'a classical needle in a classical haystack'. Since the outcome of Grover's algorithm is probabilistic - it gives the correct answer with high probability, not with certainty - the answer requires verification. For this purpose we introduce specific test states, one for each oracle. These test states can also be used to realize 'a classical search for the quantum needle' which is deterministic - it always gives a definite answer after a finite number of steps - and 3.41 times as fast as the purely classical search. Since the test-state search and Grover's algorithm look for the same quantum needle, the average number of oracle queries of the test-state search is the classical benchmark for Grover's algorithm.
Ant colony system (ACS with hybrid local search to solve vehicle routing problems
Directory of Open Access Journals (Sweden)
Suphan Sodsoon
2016-02-01
Full Text Available This research applied an Ant Colony System algorithm with a Hybrid Local Search to solve Vehicle Routing Problems (VRP from a single depot when the customers’ requirements are known. VRP is an NP-hard optimization problem and has usually been successfully solved optimum by heuristics. A fleet of vehicles of a specific capacity are used to serve a number of customers at minimum cost, without violating the constraints of vehicle capacity. There are meta-heuristic approaches to solve these problems, such as Simulated Annealing, Genetic Algorithm, Tabu Search and the Ant Colony System algorithm. In this case a hybrid local search was used (Cross-Exchange, Or-Opt and 2-Opt algorithm with an Ant Colony System algorithm. The Experimental Design was tested on 7 various problems from the data set online in the OR-Library. There are five different problems in which customers are randomly distributed with the depot in an approximately central location. The customers were grouped into clusters. The results are evaluated in terms of optimal routes using optimal distances. The experimental results are compared with those obtained from meta-heuristics and they show that the proposed method outperforms six meta-heuristics in the literature.
A Local Search Algorithm for the Flow Shop Scheduling Problem with Release Dates
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Tao Ren
2015-01-01
Full Text Available This paper discusses the flow shop scheduling problem to minimize the makespan with release dates. By resequencing the jobs, a modified heuristic algorithm is obtained for handling large-sized problems. Moreover, based on some properties, a local search scheme is provided to improve the heuristic to gain high-quality solution for moderate-sized problems. A sequence-independent lower bound is presented to evaluate the performance of the algorithms. A series of simulation results demonstrate the effectiveness of the proposed algorithms.
Self Esteem, Information Search and Problem Solving Efficiency.
1979-05-01
Weiss (1977, 1978) has shown that low self esteem workers are more likely to model the role behaviors and work values of superiors than are high self ...task where search is functional. Results showed that, as expected, low self esteem subjects searched for more information, search was functional and low ...situation. He has also argued that high self esteem individuals search for less information on problem solving tasks and are therefore less likely to
A Variable Neighborhood Search Algorithm for the Leather Nesting Problem
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Cláudio Alves
2012-01-01
Full Text Available The leather nesting problem is a cutting and packing optimization problem that consists in finding the best layout for a set of irregular pieces within a natural leather hide with an irregular surface and contour. In this paper, we address a real application of this problem related to the production of car seats in the automotive industry. The high quality requirements imposed on these products combined with the heterogeneity of the leather hides make the problem very complex to solve in practice. Very few results are reported in the literature for the leather nesting problem. Furthermore, the majority of the approaches impose some additional constraints to the layouts related to the particular application that is considered. In this paper, we describe a variable neighborhood search algorithm for the general leather nesting problem. To evaluate the performance of our approaches, we conducted an extensive set of computational experiments on real instances. The results of these experiments are reported at the end of the paper.
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J. S. Sadaghiani
2014-04-01
Full Text Available Flexible job shop scheduling problem is a key factor of using efficiently in production systems. This paper attempts to simultaneously optimize three objectives including minimization of the make span, total workload and maximum workload of jobs. Since the multi objective flexible job shop scheduling problem is strongly NP-Hard, an integrated heuristic approach has been used to solve it. The proposed approach was based on a floating search procedure that has used some heuristic algorithms. Within floating search procedure utilize local heuristic algorithms; it makes the considered problem into two sections including assigning and sequencing sub problem. First of all search is done upon assignment space achieving an acceptable solution and then search would continue on sequencing space based on a heuristic algorithm. This paper has used a multi-objective approach for producing Pareto solution. Thus proposed approach was adapted on NSGA II algorithm and evaluated Pareto-archives. The elements and parameters of the proposed algorithms were adjusted upon preliminary experiments. Finally, computational results were used to analyze efficiency of the proposed algorithm and this results showed that the proposed algorithm capable to produce efficient solutions.
Quantum algorithms for the ordered search problem via semidefinite programming
International Nuclear Information System (INIS)
Childs, Andrew M.; Landahl, Andrew J.; Parrilo, Pablo A.
2007-01-01
One of the most basic computational problems is the task of finding a desired item in an ordered list of N items. While the best classical algorithm for this problem uses log 2 N queries to the list, a quantum computer can solve the problem using a constant factor fewer queries. However, the precise value of this constant is unknown. By characterizing a class of quantum query algorithms for the ordered search problem in terms of a semidefinite program, we find quantum algorithms for small instances of the ordered search problem. Extending these algorithms to arbitrarily large instances using recursion, we show that there is an exact quantum ordered search algorithm using 4 log 605 N≅0.433 log 2 N queries, which improves upon the previously best known exact algorithm
Advanced Harmony Search with Ant Colony Optimization for Solving the Traveling Salesman Problem
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Ho-Yoeng Yun
2013-01-01
Full Text Available We propose a novel heuristic algorithm based on the methods of advanced Harmony Search and Ant Colony Optimization (AHS-ACO to effectively solve the Traveling Salesman Problem (TSP. The TSP, in general, is well known as an NP-complete problem, whose computational complexity increases exponentially by increasing the number of cities. In our algorithm, Ant Colony Optimization (ACO is used to search the local optimum in the solution space, followed by the use of the Harmony Search to escape the local optimum determined by the ACO and to move towards a global optimum. Experiments were performed to validate the efficiency of our algorithm through a comparison with other algorithms and the optimum solutions presented in the TSPLIB. The results indicate that our algorithm is capable of generating the optimum solution for most instances in the TSPLIB; moreover, our algorithm found better solutions in two cases (kroB100 and pr144 when compared with the optimum solution presented in the TSPLIB.
PFTijah: text search in an XML database system
Hiemstra, Djoerd; Rode, H.; van Os, R.; Flokstra, Jan
2006-01-01
This paper introduces the PFTijah system, a text search system that is integrated with an XML/XQuery database management system. We present examples of its use, we explain some of the system internals, and discuss plans for future work. PFTijah is part of the open source release of MonetDB/XQuery.
International Nuclear Information System (INIS)
Cui, X.; Mueller, F.; Zhang, Y.; Potok, Thomas E.
2009-01-01
Accelerating hardware devices represent a novel promise for improving the performance for many problem domains but it is not clear for which domains what accelerators are suitable. While there is no room in general-purpose processor design to significantly increase the processor frequency, developers are instead resorting to multi-core chips duplicating conventional computing capabilities on a single die. Yet, accelerators offer more radical designs with a much higher level of parallelism and novel programming environments. This present work assesses the viability of text mining on CUDA. Text mining is one of the key concepts that has become prominent as an effective means to index the Internet, but its applications range beyond this scope and extend to providing document similarity metrics, the subject of this work. We have developed and optimized text search algorithms for GPUs to exploit their potential for massive data processing. We discuss the algorithmic challenges of parallelization for text search problems on GPUs and demonstrate the potential of these devices in experiments by reporting significant speedups. Our study may be one of the first to assess more complex text search problems for suitability for GPU devices, and it may also be one of the first to exploit and report on atomic instruction usage that have recently become available in NVIDIA devices
Local Search Approaches in Stable Matching Problems
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Toby Walsh
2013-10-01
Full Text Available The stable marriage (SM problem has a wide variety of practical applications, ranging from matching resident doctors to hospitals, to matching students to schools or, more generally, to any two-sided market. In the classical formulation, n men and n women express their preferences (via a strict total order over the members of the other sex. Solving an SM problem means finding a stable marriage where stability is an envy-free notion: no man and woman who are not married to each other would both prefer each other to their partners or to being single. We consider both the classical stable marriage problem and one of its useful variations (denoted SMTI (Stable Marriage with Ties and Incomplete lists where the men and women express their preferences in the form of an incomplete preference list with ties over a subset of the members of the other sex. Matchings are permitted only with people who appear in these preference lists, and we try to find a stable matching that marries as many people as possible. Whilst the SM problem is polynomial to solve, the SMTI problem is NP-hard. We propose to tackle both problems via a local search approach, which exploits properties of the problems to reduce the size of the neighborhood and to make local moves efficiently. We empirically evaluate our algorithm for SM problems by measuring its runtime behavior and its ability to sample the lattice of all possible stable marriages. We evaluate our algorithm for SMTI problems in terms of both its runtime behavior and its ability to find a maximum cardinality stable marriage. Experimental results suggest that for SM problems, the number of steps of our algorithm grows only as O(n log(n, and that it samples very well the set of all stable marriages. It is thus a fair and efficient approach to generate stable marriages. Furthermore, our approach for SMTI problems is able to solve large problems, quickly returning stable matchings of large and often optimal size, despite the
Ancient medical texts, modern reading problems
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Maria Carlota Rosa
2006-12-01
Full Text Available The word tradition has a very specific meaning in linguistics: the passing down of a text, which may have been completed or corrected by different copyists at different times, when the concept of authorship was not the same as it is today. When reading an ancient text the word tradition must be in the reader's mind. To discuss one of the problems an ancient text poses to its modern readers, this work deals with one of the first printed medical texts in Portuguese, the Regimento proueytoso contra ha pestenença, and draws a parallel between it and two related texts, A moche profitable treatise against the pestilence, and the Recopilaçam das cousas que conuem guardar se no modo de preseruar à Cidade de Lixboa E os sãos, & curar os que esteuerem enfermos de Peste. The problems which arise out of the textual structure of those books show how difficult is to establish a tradition of another type, the medical tradition. The linguistic study of the innumerable medieval plague treatises may throw light on the continuities and on the disruptions of the so-called hippocratic-galenical medical tradition.
Solving a chemical batch scheduling problem by local search
Brucker, P.; Hurink, Johann L.
1999-01-01
A chemical batch scheduling problem is modelled in two different ways as a discrete optimization problem. Both models are used to solve the batch scheduling problem in a two-phase tabu search procedure. The method is tested on real-world data.
Search and Coherence-Building in Intuition and Insight Problem Solving
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Michael Öllinger
2017-05-01
Full Text Available Coherence-building is a key concept for a better understanding of the underlying mechanisms of intuition and insight problem solving. There are several accounts that address certain aspects of coherence-building. However, there is still no proper framework defining the general principles of coherence-building. We propose a four-stage model of coherence-building. The first stage starts with spreading activation restricted by constraints. This dynamic is a well-defined rule based process. The second stage is characterized by detecting a coherent state. We adopted a fluency account assuming that the ease of information processing indicates the realization of a coherent state. The third stage is designated to evaluate the result of the coherence-building process and assess whether the given problem is solved or not. If the coherent state does not fit the requirements of the task, the process re-enters at stage 1. These three stages characterize intuition. For insight problem solving a fourth stage is necessary, which restructures the given representation after repeated failure, so that a new search space results. The new search space enables new coherent states. We provide a review of the most important findings, outline our model, present a large number of examples, deduce potential new paradigms and measures that might help to decipher the underlying cognitive processes.
Directory of Open Access Journals (Sweden)
Shouheng Tuo
2013-01-01
Full Text Available Harmony search (HS algorithm is an emerging population-based metaheuristic algorithm, which is inspired by the music improvisation process. The HS method has been developed rapidly and applied widely during the past decade. In this paper, an improved global harmony search algorithm, named harmony search based on teaching-learning (HSTL, is presented for high dimension complex optimization problems. In HSTL algorithm, four strategies (harmony memory consideration, teaching-learning strategy, local pitch adjusting, and random mutation are employed to maintain the proper balance between convergence and population diversity, and dynamic strategy is adopted to change the parameters. The proposed HSTL algorithm is investigated and compared with three other state-of-the-art HS optimization algorithms. Furthermore, to demonstrate the robustness and convergence, the success rate and convergence analysis is also studied. The experimental results of 31 complex benchmark functions demonstrate that the HSTL method has strong convergence and robustness and has better balance capacity of space exploration and local exploitation on high dimension complex optimization problems.
Modified Cuckoo Search Algorithm for Solving Nonconvex Economic Load Dispatch Problems
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Thang Trung Nguyen
2016-01-01
Full Text Available This paper presents the application of modified cuckoo search algorithm (MCSA for solving economic load dispatch (ELD problems. The MCSA method is developed to improve the search ability and solution quality of the conventional CSA method. In the MCSA, the evaluation of eggs has divided the initial eggs into two groups, the top egg group with good quality and the abandoned group with worse quality. Moreover, the value of the updated step size in MCSA is adapted as generating a new solution for the abandoned group and the top group via the Levy flights so that a large zone is searched at the beginning and a local zone is foraged as the maximum number of iterations is nearly reached. The MCSA method has been tested on different systems with different characteristics of thermal units and constraints. The result comparison with other methods in the literature has indicated that the MCSA method can be a powerful method for solving the ELD.
Searches on star graphs and equivalent oracle problems
International Nuclear Information System (INIS)
Lee, Jaehak; Lee, Hai-Woong; Hillery, Mark
2011-01-01
We examine a search on a graph among a number of different kinds of objects (vertices), one of which we want to find. In a standard graph search, all of the vertices are the same, except for one, the marked vertex, and that is the one we wish to find. We examine the case in which the unmarked vertices can be of different types, so the background against which the search is done is not uniform. We find that the search can still be successful, but the probability of success is lower than in the uniform background case, and that probability decreases with the number of types of unmarked vertices. We also show how the graph searches can be rephrased as equivalent oracle problems.
Oscillating feature subset search algorithm for text categorization
Czech Academy of Sciences Publication Activity Database
Novovičová, Jana; Somol, Petr; Pudil, Pavel
2006-01-01
Roč. 44, č. 4225 (2006), s. 578-587 ISSN 0302-9743 R&D Projects: GA AV ČR IAA2075302; GA MŠk 2C06019 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : text classification * feature selection * oscillating search algorithm * Bhattacharyya distance Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.402, year: 2005
Müller, H-M; Van Auken, K M; Li, Y; Sternberg, P W
2018-03-09
The biomedical literature continues to grow at a rapid pace, making the challenge of knowledge retrieval and extraction ever greater. Tools that provide a means to search and mine the full text of literature thus represent an important way by which the efficiency of these processes can be improved. We describe the next generation of the Textpresso information retrieval system, Textpresso Central (TPC). TPC builds on the strengths of the original system by expanding the full text corpus to include the PubMed Central Open Access Subset (PMC OA), as well as the WormBase C. elegans bibliography. In addition, TPC allows users to create a customized corpus by uploading and processing documents of their choosing. TPC is UIMA compliant, to facilitate compatibility with external processing modules, and takes advantage of Lucene indexing and search technology for efficient handling of millions of full text documents. Like Textpresso, TPC searches can be performed using keywords and/or categories (semantically related groups of terms), but to provide better context for interpreting and validating queries, search results may now be viewed as highlighted passages in the context of full text. To facilitate biocuration efforts, TPC also allows users to select text spans from the full text and annotate them, create customized curation forms for any data type, and send resulting annotations to external curation databases. As an example of such a curation form, we describe integration of TPC with the Noctua curation tool developed by the Gene Ontology (GO) Consortium. Textpresso Central is an online literature search and curation platform that enables biocurators and biomedical researchers to search and mine the full text of literature by integrating keyword and category searches with viewing search results in the context of the full text. It also allows users to create customized curation interfaces, use those interfaces to make annotations linked to supporting evidence statements
Du, Shouqiang; Chen, Miao
2018-01-01
We consider a kind of nonsmooth optimization problems with [Formula: see text]-norm minimization, which has many applications in compressed sensing, signal reconstruction, and the related engineering problems. Using smoothing approximate techniques, this kind of nonsmooth optimization problem can be transformed into a general unconstrained optimization problem, which can be solved by the proposed smoothing modified three-term conjugate gradient method. The smoothing modified three-term conjugate gradient method is based on Polak-Ribière-Polyak conjugate gradient method. For the Polak-Ribière-Polyak conjugate gradient method has good numerical properties, the proposed method possesses the sufficient descent property without any line searches, and it is also proved to be globally convergent. Finally, the numerical experiments show the efficiency of the proposed method.
Directory of Open Access Journals (Sweden)
Ligang Cui
2013-01-01
Full Text Available The capacitated vehicle routing problem (CVRP is the most classical vehicle routing problem (VRP; many solution techniques are proposed to find its better answer. In this paper, a new improved quantum evolution algorithm (IQEA with a mixed local search procedure is proposed for solving CVRPs. First, an IQEA with a double chain quantum chromosome, new quantum rotation schemes, and self-adaptive quantum Not gate is constructed to initialize and generate feasible solutions. Then, to further strengthen IQEA's searching ability, three local search procedures 1-1 exchange, 1-0 exchange, and 2-OPT, are adopted. Experiments on a small case have been conducted to analyze the sensitivity of main parameters and compare the performances of the IQEA with different local search strategies. Together with results from the testing of CVRP benchmarks, the superiorities of the proposed algorithm over the PSO, SR-1, and SR-2 have been demonstrated. At last, a profound analysis of the experimental results is presented and some suggestions on future researches are given.
Umam, M. I. H.; Santosa, B.
2018-04-01
Combinatorial optimization has been frequently used to solve both problems in science, engineering, and commercial applications. One combinatorial problems in the field of transportation is to find a shortest travel route that can be taken from the initial point of departure to point of destination, as well as minimizing travel costs and travel time. When the distance from one (initial) node to another (destination) node is the same with the distance to travel back from destination to initial, this problems known to the Traveling Salesman Problem (TSP), otherwise it call as an Asymmetric Traveling Salesman Problem (ATSP). The most recent optimization techniques is Symbiotic Organisms Search (SOS). This paper discuss how to hybrid the SOS algorithm with variable neighborhoods search (SOS-VNS) that can be applied to solve the ATSP problem. The proposed mechanism to add the variable neighborhoods search as a local search is to generate the better initial solution and then we modify the phase of parasites with adapting mechanism of mutation. After modification, the performance of the algorithm SOS-VNS is evaluated with several data sets and then the results is compared with the best known solution and some algorithm such PSO algorithm and SOS original algorithm. The SOS-VNS algorithm shows better results based on convergence, divergence and computing time.
Blanc, Xavier; Collet, Tinh-Hai; Auer, Reto; Iriarte, Pablo; Krause, Jan; Légaré, France; Cornuz, Jacques; Clair, Carole
2015-04-07
Full-text searches of articles increase the recall, defined by the proportion of relevant publications that are retrieved. However, this method is rarely used in medical research due to resource constraints. For the purpose of a systematic review of publications addressing shared decision making, a full-text search method was required to retrieve publications where shared decision making does not appear in the title or abstract. The objective of our study was to assess the efficiency and reliability of full-text searches in major medical journals for identifying shared decision making publications. A full-text search was performed on the websites of 15 high-impact journals in general internal medicine to look up publications of any type from 1996-2011 containing the phrase "shared decision making". The search method was compared with a PubMed search of titles and abstracts only. The full-text search was further validated by requesting all publications from the same time period from the individual journal publishers and searching through the collected dataset. The full-text search for "shared decision making" on journal websites identified 1286 publications in 15 journals compared to 119 through the PubMed search. The search within the publisher-provided publications of 6 journals identified 613 publications compared to 646 with the full-text search on the respective journal websites. The concordance rate was 94.3% between both full-text searches. Full-text searching on medical journal websites is an efficient and reliable way to identify relevant articles in the field of shared decision making for review or other purposes. It may be more widely used in biomedical research in other fields in the future, with the collaboration of publishers and journals toward open-access data.
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Orhan TÜRKBEY
2002-02-01
Full Text Available Memetic algorithms, which use local search techniques, are hybrid structured algorithms like genetic algorithms among evolutionary algorithms. In this study, for Quadratic Assignment Problem (QAP, a memetic structured algorithm using a local search heuristic like 2-opt is developed. Developed in the algorithm, a crossover operator that has not been used before for QAP is applied whereas, Eshelman procedure is used in order to increase thesolution variability. The developed memetic algorithm is applied on test problems taken from QAP-LIB, the results are compared with the present techniques in the literature.
Constraint-Based Local Search for Constrained Optimum Paths Problems
Pham, Quang Dung; Deville, Yves; van Hentenryck, Pascal
Constrained Optimum Path (COP) problems arise in many real-life applications and are ubiquitous in communication networks. They have been traditionally approached by dedicated algorithms, which are often hard to extend with side constraints and to apply widely. This paper proposes a constraint-based local search (CBLS) framework for COP applications, bringing the compositionality, reuse, and extensibility at the core of CBLS and CP systems. The modeling contribution is the ability to express compositional models for various COP applications at a high level of abstraction, while cleanly separating the model and the search procedure. The main technical contribution is a connected neighborhood based on rooted spanning trees to find high-quality solutions to COP problems. The framework, implemented in COMET, is applied to Resource Constrained Shortest Path (RCSP) problems (with and without side constraints) and to the edge-disjoint paths problem (EDP). Computational results show the potential significance of the approach.
Design of an On-Line Query Language for Full Text Patent Search.
Glantz, Richard S.
The design of an English-like query language and an interactive computer environment for searching the full text of the U.S. patent collection are discussed. Special attention is paid to achieving a transparent user interface, to providing extremely broad search capabilities (including nested substitution classes, Kleene star events, and domain…
Schmidhuber, Jürgen
2013-01-01
Most of computer science focuses on automatically solving given computational problems. I focus on automatically inventing or discovering problems in a way inspired by the playful behavior of animals and humans, to train a more and more general problem solver from scratch in an unsupervised fashion. Consider the infinite set of all computable descriptions of tasks with possibly computable solutions. Given a general problem-solving architecture, at any given time, the novel algorithmic framework PowerPlay (Schmidhuber, 2011) searches the space of possible pairs of new tasks and modifications of the current problem solver, until it finds a more powerful problem solver that provably solves all previously learned tasks plus the new one, while the unmodified predecessor does not. Newly invented tasks may require to achieve a wow-effect by making previously learned skills more efficient such that they require less time and space. New skills may (partially) re-use previously learned skills. The greedy search of typical PowerPlay variants uses time-optimal program search to order candidate pairs of tasks and solver modifications by their conditional computational (time and space) complexity, given the stored experience so far. The new task and its corresponding task-solving skill are those first found and validated. This biases the search toward pairs that can be described compactly and validated quickly. The computational costs of validating new tasks need not grow with task repertoire size. Standard problem solver architectures of personal computers or neural networks tend to generalize by solving numerous tasks outside the self-invented training set; PowerPlay's ongoing search for novelty keeps breaking the generalization abilities of its present solver. This is related to Gödel's sequence of increasingly powerful formal theories based on adding formerly unprovable statements to the axioms without affecting previously provable theorems. The continually increasing
On local search for bi-objective knapsack problems.
Liefooghe, Arnaud; Paquete, Luís; Figueira, José Rui
2013-01-01
In this article, a local search approach is proposed for three variants of the bi-objective binary knapsack problem, with the aim of maximizing the total profit and minimizing the total weight. First, an experimental study on a given structural property of connectedness of the efficient set is conducted. Based on this property, a local search algorithm is proposed and its performance is compared to exact algorithms in terms of runtime and quality metrics. The experimental results indicate that this simple local search algorithm is able to find a representative set of optimal solutions in most of the cases, and in much less time than exact algorithms.
NASA Indexing Benchmarks: Evaluating Text Search Engines
Esler, Sandra L.; Nelson, Michael L.
1997-01-01
The current proliferation of on-line information resources underscores the requirement for the ability to index collections of information and search and retrieve them in a convenient manner. This study develops criteria for analytically comparing the index and search engines and presents results for a number of freely available search engines. A product of this research is a toolkit capable of automatically indexing, searching, and extracting performance statistics from each of the focused search engines. This toolkit is highly configurable and has the ability to run these benchmark tests against other engines as well. Results demonstrate that the tested search engines can be grouped into two levels. Level one engines are efficient on small to medium sized data collections, but show weaknesses when used for collections 100MB or larger. Level two search engines are recommended for data collections up to and beyond 100MB.
An Iterated Tabu Search Approach for the Clique Partitioning Problem
Directory of Open Access Journals (Sweden)
Gintaras Palubeckis
2014-01-01
all cliques induced by the subsets is as small as possible. We develop an iterated tabu search (ITS algorithm for solving this problem. The proposed algorithm incorporates tabu search, local search, and solution perturbation procedures. We report computational results on CPP instances of size up to 2000 vertices. Performance comparisons of ITS against state-of-the-art methods from the literature demonstrate the competitiveness of our approach.
Smallest-Small-World Cellular Harmony Search for Optimization of Unconstrained Benchmark Problems
Directory of Open Access Journals (Sweden)
Sung Soo Im
2013-01-01
Full Text Available We presented a new hybrid method that combines cellular harmony search algorithms with the Smallest-Small-World theory. A harmony search (HS algorithm is based on musical performance processes that occur when a musician searches for a better state of harmony. Harmony search has successfully been applied to a wide variety of practical optimization problems. Most of the previous researches have sought to improve the performance of the HS algorithm by changing the pitch adjusting rate and harmony memory considering rate. However, there has been a lack of studies to improve the performance of the algorithm by the formation of population structures. Therefore, we proposed an improved HS algorithm that uses the cellular automata formation and the topological structure of Smallest-Small-World network. The improved HS algorithm has a high clustering coefficient and a short characteristic path length, having good exploration and exploitation efficiencies. Nine benchmark functions were applied to evaluate the performance of the proposed algorithm. Unlike the existing improved HS algorithm, the proposed algorithm is expected to have improved algorithmic efficiency from the formation of the population structure.
Complicated problem solution techniques in optimal parameter searching
International Nuclear Information System (INIS)
Gergel', V.P.; Grishagin, V.A.; Rogatneva, E.A.; Strongin, R.G.; Vysotskaya, I.N.; Kukhtin, V.V.
1992-01-01
An algorithm is presented of a global search for numerical solution of multidimentional multiextremal multicriteria optimization problems with complicated constraints. A boundedness of object characteristic changes is assumed at restricted changes of its parameters (Lipschitz condition). The algorithm was realized as a computer code. The algorithm was realized as a computer code. The programme was used to solve in practice the different applied optimization problems. 10 refs.; 3 figs
A Comparison of Local Search Methods for the Multicriteria Police Districting Problem on Graph
Directory of Open Access Journals (Sweden)
F. Liberatore
2016-01-01
Full Text Available In the current economic climate, law enforcement agencies are facing resource shortages. The effective and efficient use of scarce resources is therefore of the utmost importance to provide a high standard public safety service. Optimization models specifically tailored to the necessity of police agencies can help to ameliorate their use. The Multicriteria Police Districting Problem (MC-PDP on a graph concerns the definition of sound patrolling sectors in a police district. The objective of this problem is to partition a graph into convex and continuous subsets, while ensuring efficiency and workload balance among the subsets. The model was originally formulated in collaboration with the Spanish National Police Corps. We propose for its solution three local search algorithms: a Simple Hill Climbing, a Steepest Descent Hill Climbing, and a Tabu Search. To improve their diversification capabilities, all the algorithms implement a multistart procedure, initialized by randomized greedy solutions. The algorithms are empirically tested on a case study on the Central District of Madrid. Our experiments show that the solutions identified by the novel Tabu Search outperform the other algorithms. Finally, research guidelines for future developments on the MC-PDP are given.
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A search is presented for a high-mass Higgs boson in the [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] decay modes using the ATLAS detector at the CERN Large Hadron Collider. The search uses proton-proton collision data at a centre-of-mass energy of 8 TeV corresponding to an integrated luminosity of 20.3 fb[Formula: see text]. The results of the search are interpreted in the scenario of a heavy Higgs boson with a width that is small compared with the experimental mass resolution. The Higgs boson mass range considered extends up to [Formula: see text] for all four decay modes and down to as low as 140 [Formula: see text], depending on the decay mode. No significant excess of events over the Standard Model prediction is found. A simultaneous fit to the four decay modes yields upper limits on the production cross-section of a heavy Higgs boson times the branching ratio to [Formula: see text] boson pairs. 95 % confidence level upper limits range from 0.53 pb at [Formula: see text] GeV to 0.008 pb at [Formula: see text] GeV for the gluon-fusion production mode and from 0.31 pb at [Formula: see text] GeV to 0.009 pb at [Formula: see text] GeV for the vector-boson-fusion production mode. The results are also interpreted in the context of Type-I and Type-II two-Higgs-doublet models.
Directory of Open Access Journals (Sweden)
H. Tashakkori
2016-10-01
Full Text Available Search and rescue procedures for indoor environments are quite complicated due to the fact that much of the indoor information is unavailable to rescuers before physical entrance to the incident scene. Thus, decision making regarding the number of crew required and the way they should be dispatched in the building considering the various access points and complexities in the buildings in order to cover the search area in minimum time is dependent on prior knowledge and experience of the emergency commanders. Hence, this paper introduces the Search and Rescue Problem (SRP which aims at finding best search and rescue routes that minimize the overall search time in the buildings. 3D BIM-oriented indoor GIS is integrated in the indoor route graph to find accurate routes based on the building geometric and semantic information. An Ant Colony Based Algorithm is presented that finds the number of first responders required and their individual routes to search all rooms and points of interest inside the building to minimize the overall time spent by all rescuers inside the disaster area. The evaluation of the proposed model for a case study building shows a significant improve in search and rescue time which will lead to a higher chance of saving lives and less exposure of emergency crew to danger.
Stansfield, Claire; O'Mara-Eves, Alison; Thomas, James
2017-09-01
Using text mining to aid the development of database search strings for topics described by diverse terminology has potential benefits for systematic reviews; however, methods and tools for accomplishing this are poorly covered in the research methods literature. We briefly review the literature on applications of text mining for search term development for systematic reviewing. We found that the tools can be used in 5 overarching ways: improving the precision of searches; identifying search terms to improve search sensitivity; aiding the translation of search strategies across databases; searching and screening within an integrated system; and developing objectively derived search strategies. Using a case study and selected examples, we then reflect on the utility of certain technologies (term frequency-inverse document frequency and Termine, term frequency, and clustering) in improving the precision and sensitivity of searches. Challenges in using these tools are discussed. The utility of these tools is influenced by the different capabilities of the tools, the way the tools are used, and the text that is analysed. Increased awareness of how the tools perform facilitates the further development of methods for their use in systematic reviews. Copyright © 2017 John Wiley & Sons, Ltd.
Directory of Open Access Journals (Sweden)
Mohammad Saied Fallah Niasar
2017-02-01
Full Text Available he school bus routing problem (SBRP represents a variant of the well-known vehicle routing problem. The main goal of this study is to pick up students allocated to some bus stops and generate routes, including the selected stops, in order to carry students to school. In this paper, we have proposed a simple but effective metaheuristic approach that employs two features: first, it utilizes large neighborhood structures for a deeper exploration of the search space; second, the proposed heuristic executes an efficient transition between the feasible and infeasible portions of the search space. Exploration of the infeasible area is controlled by a dynamic penalty function to convert the unfeasible solution into a feasible one. Two metaheuristics, called N-ILS (a variant of the Nearest Neighbourhood with Iterated Local Search algorithm and I-ILS (a variant of Insertion with Iterated Local Search algorithm are proposed to solve SBRP. Our experimental procedure is based on the two data sets. The results show that N-ILS is able to obtain better solutions in shorter computing times. Additionally, N-ILS appears to be very competitive in comparison with the best existing metaheuristics suggested for SBRP
Scalable Parallel Distributed Coprocessor System for Graph Searching Problems with Massive Data
Directory of Open Access Journals (Sweden)
Wanrong Huang
2017-01-01
Full Text Available The Internet applications, such as network searching, electronic commerce, and modern medical applications, produce and process massive data. Considerable data parallelism exists in computation processes of data-intensive applications. A traversal algorithm, breadth-first search (BFS, is fundamental in many graph processing applications and metrics when a graph grows in scale. A variety of scientific programming methods have been proposed for accelerating and parallelizing BFS because of the poor temporal and spatial locality caused by inherent irregular memory access patterns. However, new parallel hardware could provide better improvement for scientific methods. To address small-world graph problems, we propose a scalable and novel field-programmable gate array-based heterogeneous multicore system for scientific programming. The core is multithread for streaming processing. And the communication network InfiniBand is adopted for scalability. We design a binary search algorithm to address mapping to unify all processor addresses. Within the limits permitted by the Graph500 test bench after 1D parallel hybrid BFS algorithm testing, our 8-core and 8-thread-per-core system achieved superior performance and efficiency compared with the prior work under the same degree of parallelism. Our system is efficient not as a special acceleration unit but as a processor platform that deals with graph searching applications.
A Full-Text-Based Search Engine for Finding Highly Matched Documents Across Multiple Categories
Nguyen, Hung D.; Steele, Gynelle C.
2016-01-01
This report demonstrates the full-text-based search engine that works on any Web-based mobile application. The engine has the capability to search databases across multiple categories based on a user's queries and identify the most relevant or similar. The search results presented here were found using an Android (Google Co.) mobile device; however, it is also compatible with other mobile phones.
Local search for Steiner tree problems in graphs
Verhoeven, M.G.A.; Severens, M.E.M.; Aarts, E.H.L.; Rayward-Smith, V.J.; Reeves, C.R.; Smith, G.D.
1996-01-01
We present a local search algorithm for the Steiner tree problem in graphs, which uses a neighbourhood in which paths in a steiner tree are exchanged. The exchange function of this neigbourhood is based on multiple-source shortest path algorithm. We present computational results for a known
In search of the original text in Mark 9:38 | Hendriks | Acta Theologica
African Journals Online (AJOL)
The question remains which text appears to be the more original one. Several scholars – such as Vaganay, Duplacy, Amphoux, and others – in search of the original text of Mark – opt for a so called Western text, the main stream still prefers the Neutral text of Westcott and Hort. A text-critical analysis of Mark 9:38 may provide ...
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Demiroglu, Z S; Dozen, C; Dumanoglu, I; Girgis, S; Gokbulut, G; Guler, Y; Gurpinar, E; Hos, I; Kangal, E E; Kayis Topaksu, A; Onengut, G; Ozdemir, K; Ozturk, S; Tali, B; Topakli, H; Zorbilmez, C; Bilin, B; Bilmis, S; Isildak, B; Karapinar, G; Yalvac, M; Zeyrek, M; Gülmez, E; Kaya, M; Kaya, O; Yetkin, E A; Yetkin, T; Cakir, A; Cankocak, K; Sen, S; Vardarlı, F I; Grynyov, B; Levchuk, L; Sorokin, P; Aggleton, R; Ball, F; Beck, L; Brooke, J J; Clement, E; Cussans, D; Flacher, H; Goldstein, J; Grimes, M; Heath, G P; Heath, H F; Jacob, J; Kreczko, L; Lucas, C; Meng, Z; Newbold, D M; Paramesvaran, S; Poll, A; Sakuma, T; Seif El Nasr-Storey, S; Senkin, S; Smith, D; Smith, V J; Bell, K W; Belyaev, A; Brew, C; Brown, R M; Calligaris, L; Cieri, D; Cockerill, D J A; Coughlan, J A; Harder, K; Harper, S; Olaiya, E; Petyt, D; Shepherd-Themistocleous, C H; Thea, A; Tomalin, I R; Williams, T; Worm, S D; Baber, M; Bainbridge, R; Buchmuller, O; Bundock, A; Burton, D; Casasso, S; Citron, M; Colling, D; Corpe, L; Dauncey, P; Davies, G; De Wit, A; Della Negra, M; Dunne, P; Elwood, A; Futyan, D; Hall, G; Iles, G; Lane, R; Lucas, R; Lyons, L; Magnan, A-M; Malik, S; Nash, J; Nikitenko, A; Pela, J; Pesaresi, M; Raymond, D M; Richards, A; Rose, A; Seez, C; Tapper, A; Uchida, K; Vazquez Acosta, M; Virdee, T; Zenz, S C; Cole, J E; Hobson, P R; Khan, A; Kyberd, P; Leslie, D; Reid, I D; Symonds, P; Teodorescu, L; Turner, M; Borzou, A; Call, K; Dittmann, J; Hatakeyama, K; Liu, H; Pastika, N; Charaf, O; Cooper, S I; Henderson, C; Rumerio, P; Arcaro, D; Avetisyan, A; Bose, T; Gastler, D; Rankin, D; Richardson, C; Rohlf, J; Sulak, L; Zou, D; Alimena, J; Benelli, G; Berry, E; Cutts, D; Ferapontov, A; Garabedian, A; Hakala, J; Heintz, U; Jesus, O; Laird, E; Landsberg, G; Mao, Z; Narain, M; Piperov, S; Sagir, S; Syarif, R; Breedon, R; Breto, G; De La Barca Sanchez, M Calderon; Chauhan, S; Chertok, M; Conway, J; Conway, R; Cox, P T; Erbacher, R; Funk, G; Gardner, M; Ko, W; Lander, R; Mclean, C; Mulhearn, M; Pellett, D; Pilot, J; Ricci-Tam, F; Shalhout, S; Smith, J; Squires, M; Stolp, D; Tripathi, M; Wilbur, S; Yohay, R; Cousins, R; Everaerts, P; Florent, A; Hauser, J; Ignatenko, M; Saltzberg, D; Takasugi, E; Valuev, V; Weber, M; Burt, K; Clare, R; Ellison, J; Gary, J W; Hanson, G; Heilman, J; Ivova Paneva, M; Jandir, P; Kennedy, E; Lacroix, F; Long, O R; Malberti, M; Negrete, M Olmedo; Shrinivas, A; Wei, H; Wimpenny, S; Yates, B R; Branson, J G; Cerati, G B; Cittolin, S; D'Agnolo, R T; Derdzinski, M; Holzner, A; Kelley, R; Klein, D; Letts, J; Macneill, I; Olivito, D; Padhi, S; Pieri, M; Sani, M; Sharma, V; Simon, S; Tadel, M; Vartak, A; Wasserbaech, S; Welke, C; Würthwein, F; Yagil, A; Zevi Della Porta, G; Bradmiller-Feld, J; Campagnari, C; Dishaw, A; Dutta, V; Flowers, K; Franco Sevilla, M; Geffert, P; George, C; Golf, F; Gouskos, L; Gran, J; Incandela, J; Mccoll, N; Mullin, S D; Richman, J; Stuart, D; Suarez, I; West, C; Yoo, J; Anderson, D; Apresyan, A; Bornheim, A; Bunn, J; Chen, Y; Duarte, J; Mott, A; Newman, H B; Pena, C; Spiropulu, M; Vlimant, J R; Xie, S; Zhu, R Y; Andrews, M B; Azzolini, V; Calamba, A; Carlson, B; Ferguson, T; Paulini, M; Russ, J; Sun, M; Vogel, H; Vorobiev, I; Cumalat, J P; Ford, W T; Gaz, A; Jensen, F; Johnson, A; Krohn, M; Mulholland, T; Nauenberg, U; Stenson, K; Wagner, S R; Alexander, J; Chatterjee, A; Chaves, J; Chu, J; Dittmer, S; Eggert, N; Mirman, N; Nicolas Kaufman, G; Patterson, J R; Rinkevicius, A; Ryd, A; Skinnari, L; Soffi, L; Sun, W; Tan, S M; Teo, W D; Thom, J; Thompson, J; Tucker, J; Weng, Y; Wittich, P; Abdullin, S; Albrow, M; Apollinari, G; Banerjee, S; Bauerdick, L A T; Beretvas, A; Berryhill, J; Bhat, P C; Bolla, G; Burkett, K; Butler, J N; Cheung, H W K; Chlebana, F; Cihangir, S; Elvira, V D; Fisk, I; Freeman, J; Gottschalk, E; Gray, L; Green, D; Grünendahl, S; Gutsche, O; Hanlon, J; Hare, D; Harris, R M; Hasegawa, S; Hirschauer, J; Hu, Z; Jayatilaka, B; Jindariani, S; Johnson, M; Joshi, U; Klima, B; Kreis, B; Lammel, S; Lewis, J; Linacre, J; Lincoln, D; Lipton, R; Liu, T; Lopes De Sá, R; Lykken, J; Maeshima, K; Marraffino, J M; Maruyama, S; Mason, D; McBride, P; Merkel, P; Mrenna, S; Nahn, S; Newman-Holmes, C; O'Dell, V; Pedro, K; Prokofyev, O; Rakness, G; Sexton-Kennedy, E; Soha, A; Spalding, W J; Spiegel, L; Stoynev, S; Strobbe, N; Taylor, L; Tkaczyk, S; Tran, N V; Uplegger, L; Vaandering, E W; Vernieri, C; Verzocchi, M; Vidal, R; Wang, M; Weber, H A; Whitbeck, A; Acosta, D; Avery, P; Bortignon, P; Bourilkov, D; Brinkerhoff, A; Carnes, A; Carver, M; Curry, D; Das, S; Field, R D; Furic, I K; Konigsberg, J; Korytov, A; Kotov, K; Ma, P; Matchev, K; Mei, H; Milenovic, P; Mitselmakher, G; Rank, D; Rossin, R; Shchutska, L; Snowball, M; Sperka, D; Terentyev, N; Thomas, L; Wang, J; Wang, S; Yelton, J; Hewamanage, S; Linn, S; Markowitz, P; Martinez, G; Rodriguez, J L; Ackert, A; Adams, J R; Adams, T; Askew, A; Bein, S; Bochenek, J; Diamond, B; Haas, J; Hagopian, S; Hagopian, V; Johnson, K F; Khatiwada, A; Prosper, H; Weinberg, M; Baarmand, M M; Bhopatkar, V; Colafranceschi, S; Hohlmann, M; Kalakhety, H; Noonan, D; Roy, T; Yumiceva, F; Adams, M R; Apanasevich, L; Berry, D; Betts, R R; Bucinskaite, I; Cavanaugh, R; Evdokimov, O; Gauthier, L; Gerber, C E; Hofman, D J; Kurt, P; O'Brien, C; Sandoval Gonzalez, L D; Turner, P; Varelas, N; Wu, Z; Zakaria, M; Zhang, J; Bilki, B; Clarida, W; Dilsiz, K; Durgut, S; Gandrajula, R P; Haytmyradov, M; Khristenko, V; Merlo, J-P; Mermerkaya, H; Mestvirishvili, A; Moeller, A; Nachtman, J; Ogul, H; Onel, Y; Ozok, F; Penzo, A; Snyder, C; Tiras, E; Wetzel, J; Yi, K; Anderson, I; Barnett, B A; Blumenfeld, B; Cocoros, A; Eminizer, N; Fehling, D; Feng, L; Gritsan, A V; Maksimovic, P; Osherson, M; Roskes, J; Sarica, U; Swartz, M; Xiao, M; Xin, Y; You, C; Baringer, P; Bean, A; Bruner, C; Kenny, R P; Majumder, D; Malek, M; Mcbrayer, W; Murray, M; Sanders, S; Stringer, R; Wang, Q; Ivanov, A; Kaadze, K; Khalil, S; Makouski, M; Maravin, Y; Mohammadi, A; Saini, L K; Skhirtladze, N; Toda, S; Lange, D; Rebassoo, F; Wright, D; Anelli, C; Baden, A; Baron, O; Belloni, A; Calvert, B; Eno, S C; Ferraioli, C; Gomez, J A; Hadley, N J; Jabeen, S; Kellogg, R G; Kolberg, T; Kunkle, J; Lu, Y; Mignerey, A C; Shin, Y H; Skuja, A; Tonjes, M B; Tonwar, S C; Apyan, A; Barbieri, R; Baty, A; Bi, R; Bierwagen, K; Brandt, S; Busza, W; Cali, I A; Demiragli, Z; Di Matteo, L; Gomez Ceballos, G; Goncharov, M; Gulhan, D; Iiyama, Y; Innocenti, G M; Klute, M; Kovalskyi, D; Lai, Y S; Lee, Y-J; Levin, A; Luckey, P D; Marini, A C; Mcginn, C; Mironov, C; Narayanan, S; Niu, X; Paus, C; Roland, C; Roland, G; Salfeld-Nebgen, J; Stephans, G S F; Sumorok, K; Tatar, K; Varma, M; Velicanu, D; Veverka, J; Wang, J; Wang, T W; Wyslouch, B; Yang, M; Zhukova, V; Benvenuti, A C; Dahmes, B; Evans, A; Finkel, A; Gude, A; Hansen, P; Kalafut, S; Kao, S C; Klapoetke, K; Kubota, Y; Lesko, Z; Mans, J; Nourbakhsh, S; Ruckstuhl, N; Rusack, R; Tambe, N; Turkewitz, J; Acosta, J G; Oliveros, S; Avdeeva, E; Bartek, R; Bloom, K; Bose, S; Claes, D R; Dominguez, A; Fangmeier, C; Gonzalez Suarez, R; Kamalieddin, R; Knowlton, D; Kravchenko, I; Meier, F; Monroy, J; Ratnikov, F; Siado, J E; Snow, G R; Alyari, M; Dolen, J; George, J; Godshalk, A; Harrington, C; Iashvili, I; Kaisen, J; Kharchilava, A; Kumar, A; Rappoccio, S; Roozbahani, B; Alverson, G; Barberis, E; Baumgartel, D; Chasco, M; Hortiangtham, A; Massironi, A; Morse, D M; Nash, D; Orimoto, T; Teixeira De Lima, R; Trocino, D; Wang, R-J; Wood, D; Zhang, J; Bhattacharya, S; Hahn, K A; Kubik, A; Low, J F; Mucia, N; Odell, N; Pollack, B; Schmitt, M; Sung, K; Trovato, M; Velasco, M; Dev, N; Hildreth, M; Jessop, C; Karmgard, D J; Kellams, N; Lannon, K; Marinelli, N; Meng, F; Mueller, C; Musienko, Y; Planer, M; Reinsvold, A; Ruchti, R; Smith, G; Taroni, S; Valls, N; Wayne, M; Wolf, M; Woodard, A; Antonelli, L; Brinson, J; Bylsma, B; Durkin, L S; Flowers, S; Hart, A; Hill, C; Hughes, R; Ji, W; Ling, T Y; Liu, B; Luo, W; Puigh, D; Rodenburg, M; Winer, B L; Wulsin, H W; Driga, O; Elmer, P; 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Thomas, S; Thomassen, P; Walker, M; Foerster, M; Riley, G; Rose, K; Spanier, S; Thapa, K; Bouhali, O; Castaneda Hernandez, A; Celik, A; Dalchenko, M; De Mattia, M; Delgado, A; Dildick, S; Eusebi, R; Gilmore, J; Huang, T; Kamon, T; Krutelyov, V; Mueller, R; Osipenkov, I; Pakhotin, Y; Patel, R; Perloff, A; Rose, A; Safonov, A; Tatarinov, A; Ulmer, K A; Akchurin, N; Cowden, C; Damgov, J; Dragoiu, C; Dudero, P R; Faulkner, J; Kunori, S; Lamichhane, K; Lee, S W; Libeiro, T; Undleeb, S; Volobouev, I; Appelt, E; Delannoy, A G; Greene, S; Gurrola, A; Janjam, R; Johns, W; Maguire, C; Mao, Y; Melo, A; Ni, H; Sheldon, P; Tuo, S; Velkovska, J; Xu, Q; Arenton, M W; Cox, B; Francis, B; Goodell, J; Hirosky, R; Ledovskoy, A; Li, H; Lin, C; Neu, C; Sinthuprasith, T; Sun, X; Wang, Y; Wolfe, E; Wood, J; Xia, F; Clarke, C; Harr, R; Karchin, P E; Kottachchi Kankanamge Don, C; Lamichhane, P; Sturdy, J; Belknap, D A; Carlsmith, D; Cepeda, M; Dasu, S; Dodd, L; Duric, S; Gomber, B; Grothe, M; Herndon, M; Hervé, A; Klabbers, P; Lanaro, A; Levine, A; Long, K; Loveless, R; Mohapatra, A; Ojalvo, I; Perry, T; Pierro, G A; Polese, G; Ruggles, T; Sarangi, T; Savin, A; Sharma, A; Smith, N; Smith, W H; Taylor, D; Verwilligen, P; Woods, N; Collaboration, Authorinst The Cms
2016-01-01
A search for narrow resonances decaying to an electron and a muon is presented. The [Formula: see text] [Formula: see text] mass spectrum is also investigated for non-resonant contributions from the production of quantum black holes (QBHs). The analysis is performed using data corresponding to an integrated luminosity of 19.7[Formula: see text] collected in proton-proton collisions at a centre-of-mass energy of 8[Formula: see text] with the CMS detector at the LHC. With no evidence for physics beyond the standard model in the invariant mass spectrum of selected [Formula: see text] pairs, upper limits are set at 95 [Formula: see text] confidence level on the product of cross section and branching fraction for signals arising in theories with charged lepton flavour violation. In the search for narrow resonances, the resonant production of a [Formula: see text] sneutrino in R-parity violating supersymmetry is considered. The [Formula: see text] sneutrino is excluded for masses below 1.28[Formula: see text] for couplings [Formula: see text], and below 2.30[Formula: see text] for [Formula: see text] and [Formula: see text]. These are the most stringent limits to date from direct searches at high-energy colliders. In addition, the resonance searches are interpreted in terms of a model with heavy partners of the [Formula: see text] boson and the photon. In a framework of TeV-scale quantum gravity based on a renormalization of Newton's constant, the search for non-resonant contributions to the [Formula: see text] [Formula: see text] mass spectrum excludes QBH production below a threshold mass [Formula: see text] of 1.99[Formula: see text]. In models that invoke extra dimensions, the bounds range from 2.36[Formula: see text] for one extra dimension to 3.63[Formula: see text] for six extra dimensions. This is the first search for QBHs decaying into the [Formula: see text] [Formula: see text] final state.
Guided Text Search Using Adaptive Visual Analytics
Energy Technology Data Exchange (ETDEWEB)
Steed, Chad A [ORNL; Symons, Christopher T [ORNL; Senter, James K [ORNL; DeNap, Frank A [ORNL
2012-10-01
This research demonstrates the promise of augmenting interactive visualizations with semi- supervised machine learning techniques to improve the discovery of significant associations and insights in the search and analysis of textual information. More specifically, we have developed a system called Gryffin that hosts a unique collection of techniques that facilitate individualized investigative search pertaining to an ever-changing set of analytical questions over an indexed collection of open-source documents related to critical national infrastructure. The Gryffin client hosts dynamic displays of the search results via focus+context record listings, temporal timelines, term-frequency views, and multiple coordinate views. Furthermore, as the analyst interacts with the display, the interactions are recorded and used to label the search records. These labeled records are then used to drive semi-supervised machine learning algorithms that re-rank the unlabeled search records such that potentially relevant records are moved to the top of the record listing. Gryffin is described in the context of the daily tasks encountered at the US Department of Homeland Security s Fusion Center, with whom we are collaborating in its development. The resulting system is capable of addressing the analysts information overload that can be directly attributed to the deluge of information that must be addressed in the search and investigative analysis of textual information.
Full Text Searching and Customization in the NASA ADS Abstract Service
Eichhorn, G.; Accomazzi, A.; Grant, C. S.; Kurtz, M. J.; Henneken, E. A.; Thompson, D. M.; Murray, S. S.
2004-01-01
The NASA-ADS Abstract Service provides a sophisticated search capability for the literature in Astronomy, Planetary Sciences, Physics/Geophysics, and Space Instrumentation. The ADS is funded by NASA and access to the ADS services is free to anybody worldwide without restrictions. It allows the user to search the literature by author, title, and abstract text. The ADS database contains over 3.6 million references, with 965,000 in the Astronomy/Planetary Sciences database, and 1.6 million in the Physics/Geophysics database. 2/3 of the records have full abstracts, the rest are table of contents entries (titles and author lists only). The coverage for the Astronomy literature is better than 95% from 1975. Before that we cover all major journals and many smaller ones. Most of the journal literature is covered back to volume 1. We now get abstracts on a regular basis from most journals. Over the last year we have entered basically all conference proceedings tables of contents that are available at the Harvard Smithsonian Center for Astrophysics library. This has greatly increased the coverage of conference proceedings in the ADS. The ADS also covers the ArXiv Preprints. We download these preprints every night and index all the preprints. They can be searched either together with the other abstracts or separately. There are currently about 260,000 preprints in that database. In January 2004 we have introduced two new services, full text searching and a personal notification service called "myADS". As all other ADS services, these are free to use for anybody.
Directory of Open Access Journals (Sweden)
Vikram Kumar Kamboj
2016-04-01
Full Text Available In recent years, global warming and carbon dioxide (CO2 emission reduction have become important issues in India, as CO2 emission levels are continuing to rise in accordance with the increased volume of Indian national energy consumption under the pressure of global warming, it is crucial for Indian government to impose the effective policy to promote CO2 emission reduction. Challenge of supplying the nation with high quality and reliable electrical energy at a reasonable cost, converted government policy into deregulation and restructuring environment. This research paper presents aims to presents an effective solution for energy and environmental problems of electric power using an efficient and powerful hybrid optimization algorithm: Hybrid Harmony search-random search algorithm. The proposed algorithm is tested for standard IEEE-14 bus, -30 bus and -56 bus system. The effectiveness of proposed hybrid algorithm is compared with others well known evolutionary, heuristics and meta-heuristics search algorithms. For multi-objective unit commitment, it is found that as there are conflicting relationship between cost and emission, if the performance in cost criterion is improved, performance in the emission is seen to deteriorate.
Directory of Open Access Journals (Sweden)
Liyang Xiao
2018-03-01
Full Text Available Many government agencies and business organizations have realized that it is necessary to consider not only the economic cost but also the road transport emissions when they determine the transport policies and operations. In this study, a patient transportation problem with the aim of reducing transport emissions has been formulated by implementing CVRP model. In order to determine the routes of patient transportation with optimized emissions for targeted hospital, an improved Cuckoo Search (ICS algorithm is proposed. In this study, a ‘split’ procedure has been implemented to simplify the individual’s representation. A new category of cuckoos has been introduced to improve the ICS’s search ability. Two heuristics have been applied to improve the quality of initial population. A local search mechanism has been embedded in the search procedure to improve the quality of solutions obtained at the end of each iteration. The computational results were encouraging and demonstrated the effectiveness of the proposed solution method.
Energy Technology Data Exchange (ETDEWEB)
Crossno, Patricia Joyce; Dunlavy, Daniel M.; Stanton, Eric T.; Shead, Timothy M.
2010-09-01
This report is a summary of the accomplishments of the 'Scalable Solutions for Processing and Searching Very Large Document Collections' LDRD, which ran from FY08 through FY10. Our goal was to investigate scalable text analysis; specifically, methods for information retrieval and visualization that could scale to extremely large document collections. Towards that end, we designed, implemented, and demonstrated a scalable framework for text analysis - ParaText - as a major project deliverable. Further, we demonstrated the benefits of using visual analysis in text analysis algorithm development, improved performance of heterogeneous ensemble models in data classification problems, and the advantages of information theoretic methods in user analysis and interpretation in cross language information retrieval. The project involved 5 members of the technical staff and 3 summer interns (including one who worked two summers). It resulted in a total of 14 publications, 3 new software libraries (2 open source and 1 internal to Sandia), several new end-user software applications, and over 20 presentations. Several follow-on projects have already begun or will start in FY11, with additional projects currently in proposal.
Genetic Local Search for Optimum Multiuser Detection Problem in DS-CDMA Systems
Wang, Shaowei; Ji, Xiaoyong
Optimum multiuser detection (OMD) in direct-sequence code-division multiple access (DS-CDMA) systems is an NP-complete problem. In this paper, we present a genetic local search algorithm, which consists of an evolution strategy framework and a local improvement procedure. The evolution strategy searches the space of feasible, locally optimal solutions only. A fast iterated local search algorithm, which employs the proprietary characteristics of the OMD problem, produces local optima with great efficiency. Computer simulations show the bit error rate (BER) performance of the GLS outperforms other multiuser detectors in all cases discussed. The computation time is polynomial complexity in the number of users.
Directory of Open Access Journals (Sweden)
Zhu Xiangyang
2017-01-01
Full Text Available With the development of cloud computing, services outsourcing in clouds has become a popular business model. However, due to the fact that data storage and computing are completely outsourced to the cloud service provider, sensitive data of data owners is exposed, which could bring serious privacy disclosure. In addition, some unexpected events, such as software bugs and hardware failure, could cause incomplete or incorrect results returned from clouds. In this paper, we propose an efficient and accurate verifiable privacy-preserving multikeyword text search over encrypted cloud data based on hierarchical agglomerative clustering, which is named MUSE. In order to improve the efficiency of text searching, we proposed a novel index structure, HAC-tree, which is based on a hierarchical agglomerative clustering method and tends to gather the high-relevance documents in clusters. Based on the HAC-tree, a noncandidate pruning depth-first search algorithm is proposed, which can filter the unqualified subtrees and thus accelerate the search process. The secure inner product algorithm is used to encrypted the HAC-tree index and the query vector. Meanwhile, a completeness verification algorithm is given to verify search results. Experiment results demonstrate that the proposed method outperforms the existing works, DMRS and MRSE-HCI, in efficiency and accuracy, respectively.
Directory of Open Access Journals (Sweden)
DAHIYA, P.
2015-05-01
Full Text Available This paper presents the application of hybrid opposition based disruption operator in gravitational search algorithm (DOGSA to solve automatic generation control (AGC problem of four area hydro-thermal-gas interconnected power system. The proposed DOGSA approach combines the advantages of opposition based learning which enhances the speed of convergence and disruption operator which has the ability to further explore and exploit the search space of standard gravitational search algorithm (GSA. The addition of these two concepts to GSA increases its flexibility for solving the complex optimization problems. This paper addresses the design and performance analysis of DOGSA based proportional integral derivative (PID and fractional order proportional integral derivative (FOPID controllers for automatic generation control problem. The proposed approaches are demonstrated by comparing the results with the standard GSA, opposition learning based GSA (OGSA and disruption based GSA (DGSA. The sensitivity analysis is also carried out to study the robustness of DOGSA tuned controllers in order to accommodate variations in operating load conditions, tie-line synchronizing coefficient, time constants of governor and turbine. Further, the approaches are extended to a more realistic power system model by considering the physical constraints such as thermal turbine generation rate constraint, speed governor dead band and time delay.
Directory of Open Access Journals (Sweden)
Huixin Tian
2016-01-01
Full Text Available Different from most researches focused on the single objective hybrid flowshop scheduling (HFS problem, this paper investigates a biobjective HFS problem with sequence dependent setup time. The two objectives are the minimization of total weighted tardiness and the total setup time. To efficiently solve this problem, a Pareto-based adaptive biobjective variable neighborhood search (PABOVNS is developed. In the proposed PABOVNS, a solution is denoted as a sequence of all jobs and a decoding procedure is presented to obtain the corresponding complete schedule. In addition, the proposed PABOVNS has three major features that can guarantee a good balance of exploration and exploitation. First, an adaptive selection strategy of neighborhoods is proposed to automatically select the most promising neighborhood instead of the sequential selection strategy of canonical VNS. Second, a two phase multiobjective local search based on neighborhood search and path relinking is designed for each selected neighborhood. Third, an external archive with diversity maintenance is adopted to store the nondominated solutions and at the same time provide initial solutions for the local search. Computational results based on randomly generated instances show that the PABOVNS is efficient and even superior to some other powerful multiobjective algorithms in the literature.
International Nuclear Information System (INIS)
Athayde Costa e Silva, Marsil de; Klein, Carlos Eduardo; Mariani, Viviana Cocco; Santos Coelho, Leandro dos
2013-01-01
The environmental/economic dispatch (EED) is an important daily optimization task in the operation of many power systems. It involves the simultaneous optimization of fuel cost and emission objectives which are conflicting ones. The EED problem can be formulated as a large-scale highly constrained nonlinear multiobjective optimization problem. In recent years, many metaheuristic optimization approaches have been reported in the literature to solve the multiobjective EED. In terms of metaheuristics, recently, scatter search approaches are receiving increasing attention, because of their potential to effectively explore a wide range of complex optimization problems. This paper proposes an improved scatter search (ISS) to deal with multiobjective EED problems based on concepts of Pareto dominance and crowding distance and a new scheme for the combination method. In this paper, we have considered the standard IEEE (Institute of Electrical and Electronics Engineers) 30-bus system with 6-generators and the results obtained by proposed ISS algorithm are compared with the other recently reported results in the literature. Simulation results demonstrate that the proposed ISS algorithm is a capable candidate in solving the multiobjective EED problems. - Highlights: ► Economic dispatch. ► We solve the environmental/economic economic power dispatch problem with scatter search. ► Multiobjective scatter search can effectively improve the global search ability
A trust-based sensor allocation algorithm in cooperative space search problems
Shen, Dan; Chen, Genshe; Pham, Khanh; Blasch, Erik
2011-06-01
Sensor allocation is an important and challenging problem within the field of multi-agent systems. The sensor allocation problem involves deciding how to assign a number of targets or cells to a set of agents according to some allocation protocol. Generally, in order to make efficient allocations, we need to design mechanisms that consider both the task performers' costs for the service and the associated probability of success (POS). In our problem, the costs are the used sensor resource, and the POS is the target tracking performance. Usually, POS may be perceived differently by different agents because they typically have different standards or means of evaluating the performance of their counterparts (other sensors in the search and tracking problem). Given this, we turn to the notion of trust to capture such subjective perceptions. In our approach, we develop a trust model to construct a novel mechanism that motivates sensor agents to limit their greediness or selfishness. Then we model the sensor allocation optimization problem with trust-in-loop negotiation game and solve it using a sub-game perfect equilibrium. Numerical simulations are performed to demonstrate the trust-based sensor allocation algorithm in cooperative space situation awareness (SSA) search problems.
A rational analysis of alternating search and reflection strategies in problem solving
Taatgen, N; Shafto, MG; Langley, P
1997-01-01
In this paper two approaches to problem solving, search and reflection, are discussed, and combined in two models, both based on rational analysis (Anderson, 1990). The first model is a dynamic growth model, which shows that alternating search and reflection is a rational strategy. The second model
Directory of Open Access Journals (Sweden)
Vatutin Eduard
2017-12-01
Full Text Available The article deals with the problem of analysis of effectiveness of the heuristic methods with limited depth-first search techniques of decision obtaining in the test problem of getting the shortest path in graph. The article briefly describes the group of methods based on the limit of branches number of the combinatorial search tree and limit of analyzed subtree depth used to solve the problem. The methodology of comparing experimental data for the estimation of the quality of solutions based on the performing of computational experiments with samples of graphs with pseudo-random structure and selected vertices and arcs number using the BOINC platform is considered. It also shows description of obtained experimental results which allow to identify the areas of the preferable usage of selected subset of heuristic methods depending on the size of the problem and power of constraints. It is shown that the considered pair of methods is ineffective in the selected problem and significantly inferior to the quality of solutions that are provided by ant colony optimization method and its modification with combinatorial returns.
Directory of Open Access Journals (Sweden)
Ulrich Schäfer
2013-02-01
Full Text Available We describe a novel approach to precise searching in the full content of digital libraries. The Searchbench (for search workbench is based on sentence-wise syntactic and semantic natural language processing (NLP of both born-digital and scanned publications in PDF format. The term born-digital means natively digital, i.e. prepared electronically using typesetting systems such as LaTeX, OpenOffice, and the like. In the Searchbench, queries can be formulated as (possibly underspecified statements, consisting of simple subject-predicate-object constructs such as ‘algorithm improves word alignment’. This reduces the number of false hits in large document collections when the search words happen to appear close to each other, but are not semantically related. The method also abstracts from passive voice and predicate synonyms. Moreover, negated statements can be excluded from the search results, and negated antonym predicates again count as synonyms (e.g. not include = exclude.In the Searchbench, a sentence-semantic search can be combined with search filters for classical full-text, bibliographic metadata and automatically computed domain terms. Auto-suggest fields facilitate text input. Queries can be bookmarked or emailed. Furthermore, a novel citation browser in the Searchbench allows graphical navigation in citation networks. These have been extracted automatically from metadata and paper texts. The citation browser displays short phrases from citation sentences at the edges in the citation graph and thus allows students and researchers to quickly browse publications and immerse into a new research field. By clicking on a citation edge, the original citation sentence is shown in context, and optionally also in the original PDF layout.To showcase the usefulness of our research, we have a applied it to a collection of currently approx. 25,000 open access research papers in the field of computational linguistics and language technology, the ACL
Search for charged Higgs bosons in e+e- collisions at [Formula: see text].
Abbiendi, G; Ainsley, C; Åkesson, P F; Alexander, G; Anagnostou, G; Anderson, K J; Asai, S; Axen, D; Bailey, I; Barberio, E; Barillari, T; Barlow, R J; Batley, R J; Bechtle, P; Behnke, T; Bell, K W; Bell, P J; Bella, G; Bellerive, A; Benelli, G; Bethke, S; Biebel, O; Boeriu, O; Bock, P; Boutemeur, M; Braibant, S; Brown, R M; Burckhart, H J; Campana, S; Capiluppi, P; Carnegie, R K; Carter, A A; Carter, J R; Chang, C Y; Charlton, D G; Ciocca, C; Csilling, A; Cuffiani, M; Dado, S; Dallavalle, M; De Roeck, A; De Wolf, E A; Desch, K; Dienes, B; Dubbert, J; Duchovni, E; Duckeck, G; Duerdoth, I P; Etzion, E; Fabbri, F; Ferrari, P; Fiedler, F; Fleck, I; Ford, M; Frey, A; Gagnon, P; Gary, J W; Geich-Gimbel, C; Giacomelli, G; Giacomelli, P; Giunta, M; Goldberg, J; Gross, E; Grunhaus, J; Gruwé, M; Gupta, A; Hajdu, C; Hamann, M; Hanson, G G; Harel, A; Hauschild, M; Hawkes, C M; Hawkings, R; Herten, G; Heuer, R D; Hill, J C; Hoffman, K; Horváth, D; Igo-Kemenes, P; Ishii, K; Jeremie, H; Jovanovic, P; Junk, T R; Kanzaki, J; Karlen, D; Kawagoe, K; Kawamoto, T; Keeler, R K; Kellogg, R G; Kennedy, B W; Kluth, S; Kobayashi, T; Kobel, M; Komamiya, S; Krämer, T; Krasznahorkay, A; Krieger, P; von Krogh, J; Kuhl, T; Kupper, M; Lafferty, G D; Landsman, H; Lanske, D; Lellouch, D; Letts, J; Levinson, L; Lillich, J; Lloyd, S L; Loebinger, F K; Lu, J; Ludwig, A; Ludwig, J; Mader, W; Marcellini, S; Marchant, T E; Martin, A J; Mashimo, T; Mättig, P; McKenna, J; McPherson, R A; Meijers, F; Menges, W; Merritt, F S; Mes, H; Meyer, N; Michelini, A; Mihara, S; Mikenberg, G; Miller, D J; Mohr, W; Mori, T; Mutter, A; Nagai, K; Nakamura, I; Nanjo, H; Neal, H A; O'Neale, S W; Oh, A; Okpara, A; Oreglia, M J; Orito, S; Pahl, C; Pásztor, G; Pater, J R; Pilcher, J E; Pinfold, J; Plane, D E; Pooth, O; Przybycień, M; Quadt, A; Rabbertz, K; Rembser, C; Renkel, P; Roney, J M; Rossi, A M; Rozen, Y; Runge, K; Sachs, K; Saeki, T; Sarkisyan, E K G; Schaile, A D; Schaile, O; Scharff-Hansen, P; Schieck, J; Schörner-Sadenius, T; Schröder, M; Schumacher, M; Seuster, R; Shears, T G; Shen, B C; Sherwood, P; Skuja, A; Smith, A M; Sobie, R; Söldner-Rembold, S; Spano, F; Stahl, A; Strom, D; Ströhmer, R; Tarem, S; Tasevsky, M; Teuscher, R; Thomson, M A; Torrence, E; Toya, D; Trigger, I; Trócsányi, Z; Tsur, E; Turner-Watson, M F; Ueda, I; Ujvári, B; Vollmer, C F; Vannerem, P; Vértesi, R; Verzocchi, M; Voss, H; Vossebeld, J; Ward, C P; Ward, D R; Watkins, P M; Watson, A T; Watson, N K; Wells, P S; Wengler, T; Wermes, N; Wilson, G W; Wilson, J A; Wolf, G; Wyatt, T R; Yamashita, S; Zer-Zion, D; Zivkovic, L
A search is made for charged Higgs bosons predicted by Two-Higgs-Doublet extensions of the Standard Model (2HDM) using electron-positron collision data collected by the OPAL experiment at [Formula: see text], corresponding to an integrated luminosity of approximately 600 pb -1 . Charged Higgs bosons are assumed to be pair-produced and to decay into [Formula: see text], τν τ or AW ± . No signal is observed. Model-independent limits on the charged Higgs-boson production cross section are derived by combining these results with previous searches at lower energies. Under the assumption [Formula: see text], motivated by general 2HDM type II models, excluded areas on the [Formula: see text] plane are presented and charged Higgs bosons are excluded up to a mass of 76.3 GeV at 95 % confidence level, independent of the branching ratio BR(H ± → τν τ ). A scan of the 2HDM type I model parameter space is performed and limits on the Higgs-boson masses [Formula: see text] and m A are presented for different choices of tan β .
Improvement Of Search Process In Electronic Catalogues
Directory of Open Access Journals (Sweden)
Titas Savickas
2014-05-01
Full Text Available The paper presents investigation on search in electronic catalogues. The chosen problem domain is the search system in the electronic catalogue of Lithuanian Academic Libraries. The catalogue uses ALEPH system with MARC21 bibliographic format. The article presents analysis of problems pertaining to the current search engine and user expectations related to the search system of the electronic catalogue of academic libraries. Subsequent to analysis, the research paper presents the architecture for a semantic search system in the electronic catalogue that uses search process designed to improve search results for users.
Directory of Open Access Journals (Sweden)
Zhanzhong Wang
2018-01-01
Full Text Available The key of realizing the cross docking is to design the joint of inbound trucks and outbound trucks, so a proper sequence of trucks will make the cross-docking system much more efficient and need less makespan. A cross-docking system is proposed with multiple receiving and shipping dock doors. The objective is to find the best door assignments and the sequences of trucks in the principle of products distribution to minimize the total makespan of cross docking. To solve the problem that is regarded as a mixed integer linear programming (MILP model, three metaheuristics, namely, harmony search (HS, improved harmony search (IHS, and genetic algorithm (GA, are proposed. Furthermore, the fixed parameters are optimized by Taguchi experiments to improve the accuracy of solutions further. Finally, several numerical examples are put forward to evaluate the performances of proposed algorithms.
Neural Based Tabu Search method for solving unit commitment problem with cooling-banking constraints
Directory of Open Access Journals (Sweden)
Rajan Asir Christober Gnanakkan Charles
2009-01-01
Full Text Available This paper presents a new approach to solve short-term unit commitment problem (UCP using Neural Based Tabu Search (NBTS with cooling and banking constraints. The objective of this paper is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to find the optimal generating unit commitment in the power system for next H hours. A 7-unit utility power system in India demonstrates the effectiveness of the proposed approach; extensive studies have also been performed for different IEEE test systems consist of 10, 26 and 34 units. Numerical results are shown to compare the superiority of the cost solutions obtained using the Tabu Search (TS method, Dynamic Programming (DP and Lagrangian Relaxation (LR methods in reaching proper unit commitment.
A Novel Self-Adaptive Harmony Search Algorithm
Directory of Open Access Journals (Sweden)
Kaiping Luo
2013-01-01
Full Text Available The harmony search algorithm is a music-inspired optimization technology and has been successfully applied to diverse scientific and engineering problems. However, like other metaheuristic algorithms, it still faces two difficulties: parameter setting and finding the optimal balance between diversity and intensity in searching. This paper proposes a novel, self-adaptive search mechanism for optimization problems with continuous variables. This new variant can automatically configure the evolutionary parameters in accordance with problem characteristics, such as the scale and the boundaries, and dynamically select evolutionary strategies in accordance with its search performance. The new variant simplifies the parameter setting and efficiently solves all types of optimization problems with continuous variables. Statistical test results show that this variant is considerably robust and outperforms the original harmony search (HS, improved harmony search (IHS, and other self-adaptive variants for large-scale optimization problems and constrained problems.
Multilingual access to full text databases; Acces multilingue aux bases de donnees en texte integral
Energy Technology Data Exchange (ETDEWEB)
Fluhr, C; Radwan, K [Institut National des Sciences et Techniques Nucleaires (INSTN), Centre d` Etudes de Saclay, 91 - Gif-sur-Yvette (France)
1990-05-01
Many full text databases are available in only one language, or more, they may contain documents in different languages. Even if the user is able to understand the language of the documents in the database, it could be easier for him to express his need in his own language. For the case of databases containing documents in different languages, it is more simple to formulate the query in one language only and to retrieve documents in different languages. This paper present the developments and the first experiments of multilingual search, applied to french-english pair, for text data in nuclear field, based on the system SPIRIT. After reminding the general problems of full text databases search by queries formulated in natural language, we present the methods used to reformulate the queries and show how they can be expanded for multilingual search. The first results on data in nuclear field are presented (AFCEN norms and INIS abstracts). 4 refs.
Key word placing in Web page body text to increase visibility to search engines
Directory of Open Access Journals (Sweden)
W. T. Kritzinger
2007-11-01
Full Text Available The growth of the World Wide Web has spawned a wide variety of new information sources, which has also left users with the daunting task of determining which sources are valid. Many users rely on the Web as an information source because of the low cost of information retrieval. It is also claimed that the Web has evolved into a powerful business tool. Examples include highly popular business services such as Amazon.com and Kalahari.net. It is estimated that around 80% of users utilize search engines to locate information on the Internet. This, by implication, places emphasis on the underlying importance of Web pages being listed on search engines indices. Empirical evidence that the placement of key words in certain areas of the body text will have an influence on the Web sites' visibility to search engines could not be found in the literature. The result of two experiments indicated that key words should be concentrated towards the top, and diluted towards the bottom of a Web page to increase visibility. However, care should be taken in terms of key word density, to prevent search engine algorithms from raising the spam alarm.
Heat Transfer Search Algorithm for Non-convex Economic Dispatch Problems
Hazra, Abhik; Das, Saborni; Basu, Mousumi
2018-03-01
This paper presents Heat Transfer Search (HTS) algorithm for the non-linear economic dispatch problem. HTS algorithm is based on the law of thermodynamics and heat transfer. The proficiency of the suggested technique has been disclosed on three dissimilar complicated economic dispatch problems with valve point effect; prohibited operating zone; and multiple fuels with valve point effect. Test results acquired from the suggested technique for the economic dispatch problem have been fitted to that acquired from other stated evolutionary techniques. It has been observed that the suggested HTS carry out superior solutions.
Arasomwan, Martins Akugbe; Adewumi, Aderemi Oluyinka
2014-01-01
A new local search technique is proposed and used to improve the performance of particle swarm optimization algorithms by addressing the problem of premature convergence. In the proposed local search technique, a potential particle position in the solution search space is collectively constructed by a number of randomly selected particles in the swarm. The number of times the selection is made varies with the dimension of the optimization problem and each selected particle donates the value in the location of its randomly selected dimension from its personal best. After constructing the potential particle position, some local search is done around its neighbourhood in comparison with the current swarm global best position. It is then used to replace the global best particle position if it is found to be better; otherwise no replacement is made. Using some well-studied benchmark problems with low and high dimensions, numerical simulations were used to validate the performance of the improved algorithms. Comparisons were made with four different PSO variants, two of the variants implement different local search technique while the other two do not. Results show that the improved algorithms could obtain better quality solution while demonstrating better convergence velocity and precision, stability, robustness, and global-local search ability than the competing variants. PMID:24723827
A Group Theoretic Approach to Metaheuristic Local Search for Partitioning Problems
2005-05-01
Tabu Search. Mathematical and Computer Modeling 39: 599-616. 107 Daskin , M.S., E. Stern. 1981. A Hierarchical Objective Set Covering Model for EMS... A Group Theoretic Approach to Metaheuristic Local Search for Partitioning Problems by Gary W. Kinney Jr., B.G.S., M.S. Dissertation Presented to the...DISTRIBUTION STATEMENT A Approved for Public Release Distribution Unlimited The University of Texas at Austin May, 2005 20050504 002 REPORT
A tabu-search heuristic for solving the multi-depot vehicle scheduling problem
Directory of Open Access Journals (Sweden)
Gilmar D'Agostini Oliveira Casalinho
2014-08-01
Full Text Available Currently the logistical problems are relying quite significantly on Operational Research in order to achieve greater efficiency in their operations. Among the problems related to the vehicles scheduling in a logistics system, the Multiple Depot Vehicle Scheduling Problem (MDVSP has been addressed in several studies. The MDVSP presupposes the existence of depots that affect the planning of sequences to which travel must be performed. Often, exact methods cannot solve large instances encountered in practice and in order to take them into account, several heuristic approaches are being developed. The aim of this study was thus to solve the MDVSP using a meta-heuristic based on tabu-search method. The main motivation for this work came from the indication that only recently the use of meta-heuristics is being applied to MDVSP context (Pepin et al. 2008 and, also, the limitations listed by Rohde (2008 in his study, which used the branch-and-bound in one of the steps of the heuristic presented to solve the problem, which has increased the time resolution. The research method for solving this problem was based on adaptations of traditional techniques of Operational Research, and provided resolutions presenting very competitive results for the MDVSP such as the cost of the objective function, number of vehicles used and computational time.
Search Problems in Mission Planning and Navigation of Autonomous Aircraft. M.S. Thesis
Krozel, James A.
1988-01-01
An architecture for the control of an autonomous aircraft is presented. The architecture is a hierarchical system representing an anthropomorphic breakdown of the control problem into planner, navigator, and pilot systems. The planner system determines high level global plans from overall mission objectives. This abstract mission planning is investigated by focusing on the Traveling Salesman Problem with variations on local and global constraints. Tree search techniques are applied including the breadth first, depth first, and best first algorithms. The minimum-column and row entries for the Traveling Salesman Problem cost matrix provides a powerful heuristic to guide these search techniques. Mission planning subgoals are directed from the planner to the navigator for planning routes in mountainous terrain with threats. Terrain/threat information is abstracted into a graph of possible paths for which graph searches are performed. It is shown that paths can be well represented by a search graph based on the Voronoi diagram of points representing the vertices of mountain boundaries. A comparison of Dijkstra's dynamic programming algorithm and the A* graph search algorithm from artificial intelligence/operations research is performed for several navigation path planning examples. These examples illustrate paths that minimize a combination of distance and exposure to threats. Finally, the pilot system synthesizes the flight trajectory by creating the control commands to fly the aircraft.
CALL FOR PAPERS: Special issue on the random search problem: trends and perspectives
da Luz, Marcos G. E.; Grosberg, Alexander Y.; Raposo, Ernesto P.; Viswanathan, Gandhi M.
2008-11-01
This is a call for contributions to a special issue of Journal of Physics A: Mathematical and Theoretical dedicated to the subject of the random search problem. The motivation behind this special issue is to summarize in a single comprehensive publication, the main aspects (past and present), latest developments, different viewpoints and the directions being followed in this multidisciplinary field. We hope that such a special issue could become a particularly valuable reference for the broad scientific community working with the general random search problem. The Editorial Board has invited Marcos G E da Luz, Alexander Y Grosberg, Ernesto P Raposo and Gandhi M Viswanathan to serve as Guest Editors for the special issue. The general question of how to optimize the search for specific target objects in either continuous or discrete environments when the information available is limited is of significant importance in a broad range of fields. Representative examples include ecology (animal foraging, dispersion of populations), geology (oil recovery from mature reservoirs), information theory (automated researchers of registers in high-capacity database), molecular biology (proteins searching for their sites, e.g., on DNA ), etc. One reason underlying the richness of the random search problem relates to the `ignorance' of the locations of the randomly located `targets'. A statistical approach to the search problem can deal adequately with incomplete information and so stochastic strategies become advantageous. The general problem of how to search efficiently for randomly located target sites can thus be quantitatively described using the concepts and methods of statistical physics and stochastic processes. Scope Thus far, to the best of our knowledge, no recent textbook or review article in a physics journal has appeared on this topic. This makes a special issue with review and research articles attractive to those interested in acquiring a general introduction to the
Problems Related to the Translation of Political Texts
Directory of Open Access Journals (Sweden)
Sárosi-Márdirosz Krisztina
2015-03-01
Full Text Available This study deals with the problems related to the translation of political texts in the theoretical framework elaborated by the researchers working in the field of translation studies and reflects on the terminological peculiarities of the special language used for this text type. Consideration of the theoretical framework is followed by the analysis of a specific text spoken then written in English and translated into Hungarian and Romanian. The conclusions are intended to highlight the fact that there are no recipes for translating a political speech, because translation is not only a technical process that uses translation procedures and applies transfer operations, but also a matter of understanding cultural, historical and political situations and their significance.
Solving a large-scale precedence constrained scheduling problem with elastic jobs using tabu search
DEFF Research Database (Denmark)
Pedersen, C.R.; Rasmussen, R.V.; Andersen, Kim Allan
2007-01-01
This paper presents a solution method for minimizing makespan of a practical large-scale scheduling problem with elastic jobs. The jobs are processed on three servers and restricted by precedence constraints, time windows and capacity limitations. We derive a new method for approximating the server...... exploitation of the elastic jobs and solve the problem using a tabu search procedure. Finding an initial feasible solution is in general -complete, but the tabu search procedure includes a specialized heuristic for solving this problem. The solution method has proven to be very efficient and leads...
Directory of Open Access Journals (Sweden)
Shouheng Tuo
Full Text Available Harmony Search (HS and Teaching-Learning-Based Optimization (TLBO as new swarm intelligent optimization algorithms have received much attention in recent years. Both of them have shown outstanding performance for solving NP-Hard optimization problems. However, they also suffer dramatic performance degradation for some complex high-dimensional optimization problems. Through a lot of experiments, we find that the HS and TLBO have strong complementarity each other. The HS has strong global exploration power but low convergence speed. Reversely, the TLBO has much fast convergence speed but it is easily trapped into local search. In this work, we propose a hybrid search algorithm named HSTLBO that merges the two algorithms together for synergistically solving complex optimization problems using a self-adaptive selection strategy. In the HSTLBO, both HS and TLBO are modified with the aim of balancing the global exploration and exploitation abilities, where the HS aims mainly to explore the unknown regions and the TLBO aims to rapidly exploit high-precision solutions in the known regions. Our experimental results demonstrate better performance and faster speed than five state-of-the-art HS variants and show better exploration power than five good TLBO variants with similar run time, which illustrates that our method is promising in solving complex high-dimensional optimization problems. The experiment on portfolio optimization problems also demonstrate that the HSTLBO is effective in solving complex read-world application.
Directory of Open Access Journals (Sweden)
Behnam Barzegar
2012-01-01
Full Text Available Scheduled production system leads to avoiding stock accumulations, losses reduction, decreasing or even eliminating idol machines, and effort to better benefitting from machines for on time responding customer orders and supplying requested materials in suitable time. In flexible job-shop scheduling production systems, we could reduce time and costs by transferring and delivering operations on existing machines, that is, among NP-hard problems. The scheduling objective minimizes the maximal completion time of all the operations, which is denoted by Makespan. Different methods and algorithms have been presented for solving this problem. Having a reasonable scheduled production system has significant influence on improving effectiveness and attaining to organization goals. In this paper, new algorithm were proposed for flexible job-shop scheduling problem systems (FJSSP-GSPN that is based on gravitational search algorithm (GSA. In the proposed method, the flexible job-shop scheduling problem systems was modeled by color Petri net and CPN tool and then a scheduled job was programmed by GSA algorithm. The experimental results showed that the proposed method has reasonable performance in comparison with other algorithms.
Is Word-Problem Solving a Form of Text Comprehension?
Fuchs, Lynn S.; Fuchs, Douglas; Compton, Donald L.; Hamlett, Carol L.; Wang, Amber Y.
2015-01-01
This study's hypotheses were that (a) word-problem (WP) solving is a form of text comprehension that involves language comprehension processes, working memory, and reasoning, but (b) WP solving differs from other forms of text comprehension by requiring WP-specific language comprehension as well as general language comprehension. At the start of…
A local search for a graph clustering problem
Navrotskaya, Anna; Il'ev, Victor
2016-10-01
In the clustering problems one has to partition a given set of objects (a data set) into some subsets (called clusters) taking into consideration only similarity of the objects. One of most visual formalizations of clustering is graph clustering, that is grouping the vertices of a graph into clusters taking into consideration the edge structure of the graph whose vertices are objects and edges represent similarities between the objects. In the graph k-clustering problem the number of clusters does not exceed k and the goal is to minimize the number of edges between clusters and the number of missing edges within clusters. This problem is NP-hard for any k ≥ 2. We propose a polynomial time (2k-1)-approximation algorithm for graph k-clustering. Then we apply a local search procedure to the feasible solution found by this algorithm and hold experimental research of obtained heuristics.
Subject Retrieval from Full-Text Databases in the Humanities
East, John W.
2007-01-01
This paper examines the problems involved in subject retrieval from full-text databases of secondary materials in the humanities. Ten such databases were studied and their search functionality evaluated, focusing on factors such as Boolean operators, document surrogates, limiting by subject area, proximity operators, phrase searching, wildcards,…
A local search heuristic for the Multi-Commodity k-splittable Maximum Flow Problem
DEFF Research Database (Denmark)
Gamst, Mette
2014-01-01
, a local search heuristic for solving the problem is proposed. The heuristic is an iterative shortest path procedure on a reduced graph combined with a local search procedure to modify certain path flows and prioritize the different commodities. The heuristic is tested on benchmark instances from...
She, Hsiao-Ching; Cheng, Meng-Tzu; Li, Ta-Wei; Wang, Chia-Yu; Chiu, Hsin-Tien; Lee, Pei-Zon; Chou, Wen-Chi; Chuang, Ming-Hua
2012-01-01
This study investigates the effect of Web-based Chemistry Problem-Solving, with the attributes of Web-searching and problem-solving scaffolds, on undergraduate students' problem-solving task performance. In addition, the nature and extent of Web-searching strategies students used and its correlation with task performance and domain knowledge also…
Multilingual access to full text databases
International Nuclear Information System (INIS)
Fluhr, C.; Radwan, K.
1990-05-01
Many full text databases are available in only one language, or more, they may contain documents in different languages. Even if the user is able to understand the language of the documents in the database, it could be easier for him to express his need in his own language. For the case of databases containing documents in different languages, it is more simple to formulate the query in one language only and to retrieve documents in different languages. This paper present the developments and the first experiments of multilingual search, applied to french-english pair, for text data in nuclear field, based on the system SPIRIT. After reminding the general problems of full text databases search by queries formulated in natural language, we present the methods used to reformulate the queries and show how they can be expanded for multilingual search. The first results on data in nuclear field are presented (AFCEN norms and INIS abstracts). 4 refs
Research Proposal for Distributed Deep Web Search
Tjin-Kam-Jet, Kien
2010-01-01
This proposal identifies two main problems related to deep web search, and proposes a step by step solution for each of them. The first problem is about searching deep web content by means of a simple free-text interface (with just one input field, instead of a complex interface with many input
Monte Carlo Tree Search for Continuous and Stochastic Sequential Decision Making Problems
International Nuclear Information System (INIS)
Couetoux, Adrien
2013-01-01
In this thesis, I studied sequential decision making problems, with a focus on the unit commitment problem. Traditionally solved by dynamic programming methods, this problem is still a challenge, due to its high dimension and to the sacrifices made on the accuracy of the model to apply state of the art methods. I investigated on the applicability of Monte Carlo Tree Search methods for this problem, and other problems that are single player, stochastic and continuous sequential decision making problems. In doing so, I obtained a consistent and anytime algorithm, that can easily be combined with existing strong heuristic solvers. (author)
Solving a large-scale precedence constrained scheduling problem with elastic jobs using tabu search
DEFF Research Database (Denmark)
Pedersen, C.R.; Rasmussen, R.V.; Andersen, Kim Allan
2007-01-01
exploitation of the elastic jobs and solve the problem using a tabu search procedure. Finding an initial feasible solution is in general -complete, but the tabu search procedure includes a specialized heuristic for solving this problem. The solution method has proven to be very efficient and leads......This paper presents a solution method for minimizing makespan of a practical large-scale scheduling problem with elastic jobs. The jobs are processed on three servers and restricted by precedence constraints, time windows and capacity limitations. We derive a new method for approximating the server...... to a significant decrease in makespan compared to the strategy currently implemented....
A hybrid adaptive large neighborhood search algorithm applied to a lot-sizing problem
DEFF Research Database (Denmark)
Muller, Laurent Flindt; Spoorendonk, Simon
This paper presents a hybrid of a general heuristic framework that has been successfully applied to vehicle routing problems and a general purpose MIP solver. The framework uses local search and an adaptive procedure which choses between a set of large neighborhoods to be searched. A mixed integer...... of a solution and to investigate the feasibility of elements in such a neighborhood. The hybrid heuristic framework is applied to the multi-item capacitated lot sizing problem with dynamic lot sizes, where experiments have been conducted on a series of instances from the literature. On average the heuristic...
Iterated local search and record-to-record travel applied to the fixed charge transportation problem
DEFF Research Database (Denmark)
Andersen, Jeanne; Klose, Andreas
The fixed charge transportation problem (FCTP) is a well-known and difficult optimization problem with lots of applications in logistics. It consists in finding a minimum cost network flow from a set of suppliers to a set of customers. Beside costs proportional to quantities transported......, transportation costs do, however, include a fixed charge. Iterated local search and record-to-record travel are both simple local search based meta-heuristics that, to our knowledge, not yet have been applied to the FCTP. In this paper, we apply both types of search strategies and combine them into a single...
Liu, Yifeng; Liang, Yongjie; Wishart, David
2015-07-01
PolySearch2 (http://polysearch.ca) is an online text-mining system for identifying relationships between biomedical entities such as human diseases, genes, SNPs, proteins, drugs, metabolites, toxins, metabolic pathways, organs, tissues, subcellular organelles, positive health effects, negative health effects, drug actions, Gene Ontology terms, MeSH terms, ICD-10 medical codes, biological taxonomies and chemical taxonomies. PolySearch2 supports a generalized 'Given X, find all associated Ys' query, where X and Y can be selected from the aforementioned biomedical entities. An example query might be: 'Find all diseases associated with Bisphenol A'. To find its answers, PolySearch2 searches for associations against comprehensive collections of free-text collections, including local versions of MEDLINE abstracts, PubMed Central full-text articles, Wikipedia full-text articles and US Patent application abstracts. PolySearch2 also searches 14 widely used, text-rich biological databases such as UniProt, DrugBank and Human Metabolome Database to improve its accuracy and coverage. PolySearch2 maintains an extensive thesaurus of biological terms and exploits the latest search engine technology to rapidly retrieve relevant articles and databases records. PolySearch2 also generates, ranks and annotates associative candidates and present results with relevancy statistics and highlighted key sentences to facilitate user interpretation. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
Havva ILGIN; Derya ARSLAN
2012-01-01
In this research, by carrying out activities based on texts, effect of providing problem solving skill on students’ levels of problem solving attainment was tried to be identified. Research was performed according to pretest-posttest Experimental Model with Control Group, in 2008-2009 educational year at second grade of an elementary school in Denizli province. For nine weeks, four hours in a week, while teacher guide book was being followed in control group in Turkish language lesson, texts ...
Learning Search Algorithms: An Educational View
Directory of Open Access Journals (Sweden)
Ales Janota
2014-12-01
Full Text Available Artificial intelligence methods find their practical usage in many applications including maritime industry. The paper concentrates on the methods of uninformed and informed search, potentially usable in solving of complex problems based on the state space representation. The problem of introducing the search algorithms to newcomers has its technical and psychological dimensions. The authors show how it is possible to cope with both of them through design and use of specialized authoring systems. A typical example of searching a path through the maze is used to demonstrate how to test, observe and compare properties of various search strategies. Performance of search methods is evaluated based on the common criteria.
DEFF Research Database (Denmark)
Wen, Min; Krapper, Emil; Larsen, Jesper
things, predefined workdays, fixed starting time, maximum weekly working duration, break rule. The objective is to minimize the total delivery cost. The real-life case study is fi rst introduced and modelled as a mixed integer linear program. A multilevel variable neighborhood search heuristic...... is then proposed for the problem. At the first level, the problem size is reduced through an aggregation procedure. At the second level, the aggregated weekly planning problem is decomposed into daily planning problems, each of which is solved by a variable neighborhood search. At the last level, the solution...
Harmony search algorithm for solving combined heat and power economic dispatch problems
Energy Technology Data Exchange (ETDEWEB)
Khorram, Esmaile, E-mail: eskhor@aut.ac.i [Department of Applied Mathematics, Faculty of Mathematics and Computer Science, Amirkabir University of Technology, No. 424, Hafez Ave., 15914 Tehran (Iran, Islamic Republic of); Jaberipour, Majid, E-mail: Majid.Jaberipour@gmail.co [Department of Applied Mathematics, Faculty of Mathematics and Computer Science, Amirkabir University of Technology, No. 424, Hafez Ave., 15914 Tehran (Iran, Islamic Republic of)
2011-02-15
Economic dispatch (ED) is one of the key optimization problems in electric power system operation. The problem grows complex if one or more units produce both power and heat. Combined heat and power economic dispatch (CHPED) problem is a complicated problem that needs powerful methods to solve. This paper presents a harmony search (EDHS) algorithm to solve CHPED. Some standard examples are presented to demonstrate the effectiveness of this algorithm in obtaining the optimal solution. In all cases, the solutions obtained using EDHS algorithm are better than those obtained by other methods.
A reduced-cost iterated local search heuristic for the fixed-charge transportation problem
Buson, Erika; Roberti, Roberto; Toth, Paolo
2014-01-01
The fixed-charge transportation problem (FCTP) is a generalization of the transportation problem where an additional fixed cost is paid for sending a flow from an origin to a destination. We propose an iterated local search heuristic based on the utilization of reduced costs for guiding the restart
An improved exploratory search technique for pure integer linear programming problems
Fogle, F. R.
1990-01-01
The development is documented of a heuristic method for the solution of pure integer linear programming problems. The procedure draws its methodology from the ideas of Hooke and Jeeves type 1 and 2 exploratory searches, greedy procedures, and neighborhood searches. It uses an efficient rounding method to obtain its first feasible integer point from the optimal continuous solution obtained via the simplex method. Since this method is based entirely on simple addition or subtraction of one to each variable of a point in n-space and the subsequent comparison of candidate solutions to a given set of constraints, it facilitates significant complexity improvements over existing techniques. It also obtains the same optimal solution found by the branch-and-bound technique in 44 of 45 small to moderate size test problems. Two example problems are worked in detail to show the inner workings of the method. Furthermore, using an established weighted scheme for comparing computational effort involved in an algorithm, a comparison of this algorithm is made to the more established and rigorous branch-and-bound method. A computer implementation of the procedure, in PC compatible Pascal, is also presented and discussed.
Exploration of the search space of the in-core fuel management problem by knowledge-based techniques
International Nuclear Information System (INIS)
Galperin, A.
1995-01-01
The process of generating reload configuration patterns is presented as a search procedure. The search space of the problem is found to contain ∼ 10 12 possible problem states. If computational resources and execution time necessary to evaluate a single solution are taken into account, this problem may be described as a ''large space search problem.'' Understanding of the structure of the search space, i.e., distribution of the optimal (or nearly optimal) solutions, is necessary to choose an appropriate search method and to utilize adequately domain heuristic knowledge. A worth function is developed based on two performance parameters: cycle length and power peaking factor. A series of numerical experiments was carried out; 300,000 patterns were generated in 40 sessions. All these patterns were analyzed by simulating the power production cycle and by evaluating the two performance parameters. The worth function was calculated and plotted. Analysis of the worth function reveals quite a complicated search space structure. The fine structure shows an extremely large number of local peaks: about one peak per hundred configurations. The direct implication of this discovery is that within a search space of 10 12 states, there are ∼10 10 local optima. Further consideration of the worth function shape shows that the distribution of the local optima forms a contour with much slower variations, where ''better'' or ''worse'' groups of patterns are spaced within a few thousand or tens of thousands of configurations, and finally very broad subregions of the whole space display variations of the worth function, where optimal regions include tens of thousands of patterns and are separated by hundreds of thousands and millions
Learning to Solve Problems by Searching for Macro-Operators
1983-07-01
executing generalized robot plans. Aritificial Intelligence 3:25 1-288, 1972. [Frey 821 Frey, Alexander Ii. Jr., and David Singmaster. Handbook of Cubik...and that searching for macros may be a useful general learning paradigm. 1.1. Introduction One view of die die field of artificial intelligence is that... intelligence literature [Schofield 67, Gaschnig 79, Ericsson 761 and provides one of the simplest examples of the operation of the Macro Problem Solver. It
ASCOT: a text mining-based web-service for efficient search and assisted creation of clinical trials
2012-01-01
Clinical trials are mandatory protocols describing medical research on humans and among the most valuable sources of medical practice evidence. Searching for trials relevant to some query is laborious due to the immense number of existing protocols. Apart from search, writing new trials includes composing detailed eligibility criteria, which might be time-consuming, especially for new researchers. In this paper we present ASCOT, an efficient search application customised for clinical trials. ASCOT uses text mining and data mining methods to enrich clinical trials with metadata, that in turn serve as effective tools to narrow down search. In addition, ASCOT integrates a component for recommending eligibility criteria based on a set of selected protocols. PMID:22595088
A Bayesian network approach to the database search problem in criminal proceedings
2012-01-01
Background The ‘database search problem’, that is, the strengthening of a case - in terms of probative value - against an individual who is found as a result of a database search, has been approached during the last two decades with substantial mathematical analyses, accompanied by lively debate and centrally opposing conclusions. This represents a challenging obstacle in teaching but also hinders a balanced and coherent discussion of the topic within the wider scientific and legal community. This paper revisits and tracks the associated mathematical analyses in terms of Bayesian networks. Their derivation and discussion for capturing probabilistic arguments that explain the database search problem are outlined in detail. The resulting Bayesian networks offer a distinct view on the main debated issues, along with further clarity. Methods As a general framework for representing and analyzing formal arguments in probabilistic reasoning about uncertain target propositions (that is, whether or not a given individual is the source of a crime stain), this paper relies on graphical probability models, in particular, Bayesian networks. This graphical probability modeling approach is used to capture, within a single model, a series of key variables, such as the number of individuals in a database, the size of the population of potential crime stain sources, and the rarity of the corresponding analytical characteristics in a relevant population. Results This paper demonstrates the feasibility of deriving Bayesian network structures for analyzing, representing, and tracking the database search problem. The output of the proposed models can be shown to agree with existing but exclusively formulaic approaches. Conclusions The proposed Bayesian networks allow one to capture and analyze the currently most well-supported but reputedly counter-intuitive and difficult solution to the database search problem in a way that goes beyond the traditional, purely formulaic expressions
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A search for Higgs boson pair production [Formula: see text] is performed with 19.5 fb[Formula: see text] of proton-proton collision data at [Formula: see text] TeV, which were recorded by the ATLAS detector at the Large Hadron Collider in 2012. The decay products of each Higgs boson are reconstructed as a high-momentum [Formula: see text] system with either a pair of small-radius jets or a single large-radius jet, the latter exploiting jet substructure techniques and associated b -tagged track-jets. No evidence for resonant or non-resonant Higgs boson pair production is observed. The data are interpreted in the context of the Randall-Sundrum model with a warped extra dimension as well as the two-Higgs-doublet model. An upper limit on the cross-section for [Formula: see text] of 3.2 (2.3) fb is set for a Kaluza-Klein graviton [Formula: see text] mass of 1.0 (1.5) TeV, at the 95 % confidence level. The search for non-resonant Standard Model hh production sets an observed 95 % confidence level upper limit on the production cross-section [Formula: see text] of 202 fb, compared to a Standard Model prediction of [Formula: see text] fb.
Automatic Contextual Text Correction Using The Linguistic Habits Graph Lhg
Directory of Open Access Journals (Sweden)
Marcin Gadamer
2009-01-01
Full Text Available Automatic text correction is an essential problem of today text processors and editors. Thispaper introduces a novel algorithm for automation of contextual text correction using a LinguisticHabit Graph (LHG also introduced in this paper. A specialist internet crawler hasbeen constructed for searching through web sites in order to build a Linguistic Habit Graphafter text corpuses gathered in polish web sites. The achieved correction results on a basis ofthis algorithm using this LHG were compared with commercial programs which also enableto make text correction: Microsoft Word 2007, Open Office Writer 3.0 and search engineGoogle. The achieved results of text correction were much better than correction made bythese commercial tools.
Directory of Open Access Journals (Sweden)
Hailong Wang
2018-01-01
Full Text Available The backtracking search optimization algorithm (BSA is a population-based evolutionary algorithm for numerical optimization problems. BSA has a powerful global exploration capacity while its local exploitation capability is relatively poor. This affects the convergence speed of the algorithm. In this paper, we propose a modified BSA inspired by simulated annealing (BSAISA to overcome the deficiency of BSA. In the BSAISA, the amplitude control factor (F is modified based on the Metropolis criterion in simulated annealing. The redesigned F could be adaptively decreased as the number of iterations increases and it does not introduce extra parameters. A self-adaptive ε-constrained method is used to handle the strict constraints. We compared the performance of the proposed BSAISA with BSA and other well-known algorithms when solving thirteen constrained benchmarks and five engineering design problems. The simulation results demonstrated that BSAISA is more effective than BSA and more competitive with other well-known algorithms in terms of convergence speed.
Identifying vehicle descriptions in microblogging text with the aim of reducing or predicting crime
CSIR Research Space (South Africa)
Featherstone, Coral
2013-11-01
Full Text Available in the fight against crime, to the specific problem of identifying the description of vehicles in microblog text. As this problem has many aspects, especially in terms of data gathering and identification, an initial search is performed on preset keywords...
Searching spectrum points of difference initial-boundary value problems with using GAS
International Nuclear Information System (INIS)
Mazepa, N.E.
1989-01-01
A new algorithm for searching spectrum points is proposed. The difference schemes which approximate systems of linear differential equations of hyperbolic type with constant coefficients and in one space dimension are considered. For important class of practiclas problems this algorithm reduces the hard spectrum calculation problem to the polynomial equation solution. For complicated analytic manipulations connected with realization of this algorithm the computation algebraic system REDUCE is used. 28 refs
SGML-Based Markup for Literary Texts: Two Problems and Some Solutions.
Barnard, David; And Others
1988-01-01
Identifies the Standard Generalized Markup Language (SGML) as the best basis for a markup standard for encoding literary texts. Outlines solutions to problems using SGML and discusses the problem of maintaining multiple views of a document. Examines several ways of reducing the burden of markups. (GEA)
PHILOSOPHICAL-ANTROPOLOGICAL ASPECTS OF A PROBLEM OF SEARCH EXTRA-TERRESTRIAL OF CIVILIZATIONS
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A. T. Tshedrin
2013-09-01
Full Text Available Purpose. The fears express, that «METI-projects», which testify to existence of mankind as technicalgeneous of a civilization for highly advanced ETC of a Galaxy, can have the extremely negative consequences, and «SETI-projects» and received radiosignals can become the information weapon aggressive ETC. The analysis of these fears as complete sociocultural of a phenomenon, them philosophical-anthropological of measurement, sociocultural of the basis, the forms of their display are the purpose of clause. Methodology. Author used the social-communicative approach, methods of system and cluster analyses. Scientific innovation. Are opened philosophical-anthropological of measurement of a problem of life extra-terrestrial intelligents (ETI, the factors of statement of a problem of contacts with ETC in the modern form connected with spacing of scientific and technical activity of mankind, influence of processes globalization on philosophical-anthropological aspects of a problem ETC, connected with changes in the fundamental relation «the Man - World» are investigated. These processes conduct to growth of fears concerning unpredictable intervention in terrestrial sociocultural system of alien reason. The persuasive fears, connected with possible consequences of contacts with ETC, take the form of hypotheses rather extra-terrestrial of artificial intelligence (ETAI as potential subject of space contact. The positive and negative scripts of dialogue with ETAI, problem «of high quality of a signal» and «SETI-hacker», connected with ETAI as by the subject of space dialogue are considered. Conclusions. The further development of a problem of search ETC and establishment of contacts with it will be connected, on the one hand to success in overcoming civilization of impasse, in which there was a mankind on a boundary ХХ – ХХI of centuries, and with another - deepening of revolution in cosmology, progress of observant astronomy, philosophical
Directory of Open Access Journals (Sweden)
A. P. Karpenko
2015-01-01
Full Text Available We consider the relatively new and rapidly developing class of methods to solve a problem of multi-objective optimization, based on the preliminary built finite-dimensional approximation of the set, and thereby, the Pareto front of this problem as well. The work investigates the efficiency of several modifications of the method of adaptive weighted sum (AWS. This method proposed in the paper of Ryu and Kim Van (JH. Ryu, S. Kim, H. Wan is intended to build Pareto approximation of the multi-objective optimization problem.The AWS method uses quadratic approximation of the objective functions in the current sub-domain of the search space (the area of trust based on the gradient and Hessian matrix of the objective functions. To build the (quadratic meta objective functions this work uses methods of the experimental design theory, which involves calculating the values of these functions in the grid nodes covering the area of trust (a sensing method of the search domain. There are two groups of the sensing methods under consideration: hypercube- and hyper-sphere-based methods. For each of these groups, a number of test multi-objective optimization tasks has been used to study the efficiency of the following grids: "Latin Hypercube"; grid, which is uniformly random for each measurement; grid, based on the LP sequences.
A Rule-Based Local Search Algorithm for General Shift Design Problems in Airport Ground Handling
DEFF Research Database (Denmark)
Clausen, Tommy
We consider a generalized version of the shift design problem where shifts are created to cover a multiskilled demand and fit the parameters of the workforce. We present a collection of constraints and objectives for the generalized shift design problem. A local search solution framework with mul......We consider a generalized version of the shift design problem where shifts are created to cover a multiskilled demand and fit the parameters of the workforce. We present a collection of constraints and objectives for the generalized shift design problem. A local search solution framework...... with multiple neighborhoods and a loosely coupled rule engine based on simulated annealing is presented. Computational experiments on real-life data from various airport ground handling organization show the performance and flexibility of the proposed algorithm....
Visual Representation Determines Search Difficulty: Explaining Visual Search Asymmetries
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Neil eBruce
2011-07-01
Full Text Available In visual search experiments there exist a variety of experimental paradigms in which a symmetric set of experimental conditions yields asymmetric corresponding task performance. There are a variety of examples of this that currently lack a satisfactory explanation. In this paper, we demonstrate that distinct classes of asymmetries may be explained by virtue of a few simple conditions that are consistent with current thinking surrounding computational modeling of visual search and coding in the primate brain. This includes a detailed look at the role that stimulus familiarity plays in the determination of search performance. Overall, we demonstrate that all of these asymmetries have a common origin, namely, they are a consequence of the encoding that appears in the visual cortex. The analysis associated with these cases yields insight into the problem of visual search in general and predictions of novel search asymmetries.
International Nuclear Information System (INIS)
Tavakkoli-Moghaddam, R.
1999-01-01
This paper present unequal-sized facilities layout solutions generated by a genetic search program. named Layout Design using a Genetic Algorithm) 9. The generalized quadratic assignment problem requiring pre-determined distance and material flow matrices as the input data and the continuous plane model employing a dynamic distance measure and a material flow matrix are discussed. Computational results on test problems are reported as compared with layout solutions generated by the branch - and bound algorithm a hybrid method merging simulated annealing and local search techniques, and an optimization process of an enveloped block
Putting Continuous Metaheuristics to Work in Binary Search Spaces
Directory of Open Access Journals (Sweden)
Broderick Crawford
2017-01-01
Full Text Available In the real world, there are a number of optimization problems whose search space is restricted to take binary values; however, there are many continuous metaheuristics with good results in continuous search spaces. These algorithms must be adapted to solve binary problems. This paper surveys articles focused on the binarization of metaheuristics designed for continuous optimization.
Directory of Open Access Journals (Sweden)
Weizhen Rao
2016-01-01
Full Text Available The classical model of vehicle routing problem (VRP generally minimizes either the total vehicle travelling distance or the total number of dispatched vehicles. Due to the increased importance of environmental sustainability, one variant of VRPs that minimizes the total vehicle fuel consumption has gained much attention. The resulting fuel consumption VRP (FCVRP becomes increasingly important yet difficult. We present a mixed integer programming model for the FCVRP, and fuel consumption is measured through the degree of road gradient. Complexity analysis of FCVRP is presented through analogy with the capacitated VRP. To tackle the FCVRP’s computational intractability, we propose an efficient two-objective hybrid local search algorithm (TOHLS. TOHLS is based on a hybrid local search algorithm (HLS that is also used to solve FCVRP. Based on the Golden CVRP benchmarks, 60 FCVRP instances are generated and tested. Finally, the computational results show that the proposed TOHLS significantly outperforms the HLS.
Is Word-Problem Solving a Form of Text Comprehension?
Fuchs, Lynn S.; Fuchs, Douglas; Compton, Donald L.; Hamlett, Carol L.; Wang, Amber Y.
2015-01-01
This study’s hypotheses were that (a) word-problem (WP) solving is a form of text comprehension that involves language comprehension processes, working memory, and reasoning, but (b) WP solving differs from other forms of text comprehension by requiring WP-specific language comprehension as well as general language comprehension. At the start of the 2nd grade, children (n = 206; on average, 7 years, 6 months) were assessed on general language comprehension, working memory, nonlinguistic reasoning, processing speed (a control variable), and foundational skill (arithmetic for WPs; word reading for text comprehension). In spring, they were assessed on WP-specific language comprehension, WPs, and text comprehension. Path analytic mediation analysis indicated that effects of general language comprehension on text comprehension were entirely direct, whereas effects of general language comprehension on WPs were partially mediated by WP-specific language. By contrast, effects of working memory and reasoning operated in parallel ways for both outcomes. PMID:25866461
Tabu search approaches for the multi-level warehouse layout problem with adjacency constraints
Zhang, G. Q.; Lai, K. K.
2010-08-01
A new multi-level warehouse layout problem, the multi-level warehouse layout problem with adjacency constraints (MLWLPAC), is investigated. The same item type is required to be located in adjacent cells, and horizontal and vertical unit travel costs are product dependent. An integer programming model is proposed to formulate the problem, which is NP hard. Along with a cube-per-order index policy based heuristic, the standard tabu search (TS), greedy TS, and dynamic neighbourhood based TS are presented to solve the problem. The computational results show that the proposed approaches can reduce the transportation cost significantly.
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MANAR Y. KASHMOLA
2012-06-01
Full Text Available The development of hybrid algorithms for solving complex optimization problems focuses on enhancing the strengths and compensating for the weakness of two or more complementary approaches. The goal is to intelligently combine the key elements of these approaches to find superior solutions to solve optimization problems. Optimal routing in communication network is considering a complex optimization problem. In this paper we propose a hybrid Hopfield Neural Network (HNN and Tabu Search (TS algorithm, this algorithm called hybrid HNN-TS algorithm. The paradigm of this hybridization is embedded. We embed the short-term memory and tabu restriction features from TS algorithm in the HNN model. The short-term memory and tabu restriction control the neuron selection process in the HNN model in order to get around the local minima problem and find an optimal solution using the HNN model to solve complex optimization problem. The proposed algorithm is intended to find the optimal path for packet transmission in the network which is fills in the field of routing problem. The optimal path that will be selected is depending on 4-tuples (delay, cost, reliability and capacity. Test results show that the propose algorithm can find path with optimal cost and a reasonable number of iterations. It also shows that the complexity of the network model won’t be a problem since the neuron selection is done heuristically.
A meta-heuristic method for solving scheduling problem: crow search algorithm
Adhi, Antono; Santosa, Budi; Siswanto, Nurhadi
2018-04-01
Scheduling is one of the most important processes in an industry both in manufacturingand services. The scheduling process is the process of selecting resources to perform an operation on tasks. Resources can be machines, peoples, tasks, jobs or operations.. The selection of optimum sequence of jobs from a permutation is an essential issue in every research in scheduling problem. Optimum sequence becomes optimum solution to resolve scheduling problem. Scheduling problem becomes NP-hard problem since the number of job in the sequence is more than normal number can be processed by exact algorithm. In order to obtain optimum results, it needs a method with capability to solve complex scheduling problems in an acceptable time. Meta-heuristic is a method usually used to solve scheduling problem. The recently published method called Crow Search Algorithm (CSA) is adopted in this research to solve scheduling problem. CSA is an evolutionary meta-heuristic method which is based on the behavior in flocks of crow. The calculation result of CSA for solving scheduling problem is compared with other algorithms. From the comparison, it is found that CSA has better performance in term of optimum solution and time calculation than other algorithms.
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Spiwoks, R; Spousta, M; Spreitzer, T; Spurlock, B; St Denis, R D; Stahlman, J; Stamen, R; Stanecka, E; Stanek, R W; Stanescu, C; Stanescu-Bellu, M; Stapnes, S; Starchenko, E A; Stark, J; Staroba, P; Starovoitov, P; Staszewski, R; Staude, A; Stavina, P; Steele, G; Steinbach, P; Steinberg, P; Stekl, I; Stelzer, B; Stelzer, H J; Stelzer-Chilton, O; Stenzel, H; Stern, S; Stewart, G A; Stillings, J A; Stockton, M C; Stoerig, K; Stoicea, G; Stonjek, S; Strachota, P; Stradling, A R; Straessner, A; Strandberg, J; Strandberg, S; Strandlie, A; Strang, M; Strauss, E; Strauss, M; Strizenec, P; Ströhmer, R; Strom, D M; Strong, J A; Stroynowski, R; Strube, J; Stugu, B; Stumer, I; Stupak, J; Sturm, P; Styles, N A; Soh, D A; Su, D; Subramania, Hs; Succurro, A; Sugaya, Y; Suhr, C; Suk, M; Sulin, V V; Sultansoy, S; Sumida, T; Sun, X; Sundermann, J E; Suruliz, K; Susinno, G; Sutton, M R; Suzuki, Y; Suzuki, Y; Svatos, M; Swedish, S; Sykora, I; Sykora, T; Sánchez, J; Ta, D; Tackmann, K; Taffard, A; Tafirout, R; Taiblum, N; Takahashi, Y; Takai, H; Takashima, R; Takeda, H; Takeshita, T; Takubo, Y; Talby, M; Talyshev, A; Tamsett, M C; Tanaka, J; Tanaka, R; Tanaka, S; Tanaka, S; Tanasijczuk, A J; Tani, K; Tannoury, N; Tapprogge, S; Tardif, D; Tarem, S; Tarrade, F; Tartarelli, G F; Tas, P; Tasevsky, M; Tassi, E; Tatarkhanov, M; Tayalati, Y; Taylor, C; Taylor, F E; Taylor, G N; Taylor, W; Teinturier, M; Teixeira Dias Castanheira, M; Teixeira-Dias, P; Temming, K K; Ten Kate, H; Teng, P K; Terada, S; Terashi, K; Terron, J; Testa, M; Teuscher, R J; Therhaag, J; Theveneaux-Pelzer, T; Thoma, S; Thomas, J P; Thompson, E N; Thompson, P D; Thompson, P D; Thompson, A S; Thomsen, L A; Thomson, E; Thomson, M; Thun, R P; Tian, F; Tibbetts, M J; Tic, T; Tikhomirov, V O; Tikhonov, Y A; Timoshenko, S; Tipton, P; Tique Aires Viegas, F J; Tisserant, S; Todorov, T; Todorova-Nova, S; Toggerson, B; Tojo, J; Tokár, S; Tokushuku, K; Tollefson, K; Tomoto, M; Tompkins, L; Toms, K; Tonoyan, A; Topfel, C; Topilin, N D; Torchiani, I; 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A search for top quark pair resonances in final states containing at least one electron or muon has been performed with the ATLAS experiment at the CERN Large Hadron Collider. The search uses a data sample corresponding to an integrated luminosity of 2.05 fb -1 , which was recorded in 2011 at a proton-proton centre-of-mass energy of 7 TeV. No evidence for a resonance is found and limits are set on the production cross-section times branching ratio to [Formula: see text] for narrow and wide resonances. For narrow Z ' bosons, the observed 95 % Bayesian credibility level limits range from 9.3 pb to 0.95 pb for masses in the range of m Z ' =500 GeV to m Z ' =1300 GeV. The corresponding excluded mass region for a leptophobic topcolour Z ' boson (Kaluza-Klein gluon excitation in the Randall-Sundrum model) is m Z ' <880 GeV ([Formula: see text]).
Bula, Gustavo Alfredo; Prodhon, Caroline; Gonzalez, Fabio Augusto; Afsar, H Murat; Velasco, Nubia
2017-02-15
This work focuses on the Heterogeneous Fleet Vehicle Routing problem (HFVRP) in the context of hazardous materials (HazMat) transportation. The objective is to determine a set of routes that minimizes the total expected routing risk. This is a nonlinear function, and it depends on the vehicle load and the population exposed when an incident occurs. Thus, a piecewise linear approximation is used to estimate it. For solving the problem, a variant of the Variable Neighborhood Search (VNS) algorithm is employed. To improve its performance, a post-optimization procedure is implemented via a Set Partitioning (SP) problem. The SP is solved on a pool of routes obtained from executions of the local search procedure embedded on the VNS. The algorithm is tested on two sets of HFVRP instances based on literature with up to 100 nodes, these instances are modified to include vehicle and arc risk parameters. The results are competitive in terms of computational efficiency and quality attested by a comparison with Mixed Integer Linear Programming (MILP) previously proposed. Copyright © 2016 Elsevier B.V. All rights reserved.
Onebox: Free-Text Interfaces as an Alternative to Complex Web Forms
Tjin-Kam-Jet, Kien; Trieschnigg, Rudolf Berend; Hiemstra, Djoerd
2011-01-01
This paper investigates the problem of translating free-text queries into key-value pairs as an alternative means for searching `behind' web forms. We introduce a novel specication language for specifying free-text interfaces, and report the results of a user study where we evaluated our prototype
Collective search by ants in microgravity
Directory of Open Access Journals (Sweden)
Stefanie M. Countryman
2015-03-01
Full Text Available The problem of collective search is a tradeoff between searching thoroughly and covering as much area as possible. This tradeoff depends on the density of searchers. Solutions to the problem of collective search are currently of much interest in robotics and in the study of distributed algorithms, for example to design ways that without central control robots can use local information to perform search and rescue operations. Ant colonies operate without central control. Because they can perceive only local, mostly chemical and tactile cues, they must search collectively to find resources and to monitor the colony's environment. Examining how ants in diverse environments solve the problem of collective search can elucidate how evolution has led to diverse forms of collective behavior. An experiment on the International Space Station in January 2014 examined how ants (Tetramorium caespitum perform collective search in microgravity. In the ISS experiment, the ants explored a small arena in which a barrier was lowered to increase the area and thus lower ant density. In microgravity, relative to ground controls, ants explored the area less thoroughly and took more convoluted paths. It appears that the difficulty of holding on to the surface interfered with the ants’ ability to search collectively. Ants frequently lost contact with the surface, but showed a remarkable ability to regain contact with the surface.
Application of Tabu Search Algorithm in Job Shop Scheduling
Directory of Open Access Journals (Sweden)
Betrianis Betrianis
2010-10-01
Full Text Available Tabu Search is one of local search methods which is used to solve the combinatorial optimization problem. This method aimed is to make the searching process of the best solution in a complex combinatorial optimization problem(np hard, ex : job shop scheduling problem, became more effective, in a less computational time but with no guarantee to optimum solution.In this paper, tabu search is used to solve the job shop scheduling problem consists of 3 (three cases, which is ordering package of September, October and November with objective of minimizing makespan (Cmax. For each ordering package, there is a combination for initial solution and tabu list length. These result then compared with 4 (four other methods using basic dispatching rules such as Shortest Processing Time (SPT, Earliest Due Date (EDD, Most Work Remaining (MWKR dan First Come First Served (FCFS. Scheduling used Tabu Search Algorithm is sensitive for variables changes and gives makespan shorter than scheduling used by other four methods.
Optimization of travel salesman problem using the ant colony system and Greedy search
International Nuclear Information System (INIS)
Esquivel E, J.; Ordonez A, A.; Ortiz S, J. J.
2008-01-01
In this paper we present some results obtained during the development of optimization systems that can be used to design refueling and patterns of control rods in a BWR. These systems use ant colonies and Greedy search. The first phase of this project is to be familiar with these optimization techniques applied to the problem of travel salesman problem (TSP). The utility of TSP study is that, like the refueling design and pattern design of control rods are problems of combinative optimization. Even, the similarity with the problem of the refueling design is remarkable. It is presented some results for the TSP with the 32 state capitals of Mexico country. (Author)
Tashakkori, H.; Rajabifard, A.; Kalantari, M.
2016-10-01
Search and rescue procedures for indoor environments are quite complicated due to the fact that much of the indoor information is unavailable to rescuers before physical entrance to the incident scene. Thus, decision making regarding the number of crew required and the way they should be dispatched in the building considering the various access points and complexities in the buildings in order to cover the search area in minimum time is dependent on prior knowledge and experience of the emergency commanders. Hence, this paper introduces the Search and Rescue Problem (SRP) which aims at finding best search and rescue routes that minimize the overall search time in the buildings. 3D BIM-oriented indoor GIS is integrated in the indoor route graph to find accurate routes based on the building geometric and semantic information. An Ant Colony Based Algorithm is presented that finds the number of first responders required and their individual routes to search all rooms and points of interest inside the building to minimize the overall time spent by all rescuers inside the disaster area. The evaluation of the proposed model for a case study building shows a significant improve in search and rescue time which will lead to a higher chance of saving lives and less exposure of emergency crew to danger.
Three hybridization models based on local search scheme for job shop scheduling problem
Balbi Fraga, Tatiana
2015-05-01
This work presents three different hybridization models based on the general schema of Local Search Heuristics, named Hybrid Successive Application, Hybrid Neighborhood, and Hybrid Improved Neighborhood. Despite similar approaches might have already been presented in the literature in other contexts, in this work these models are applied to analyzes the solution of the job shop scheduling problem, with the heuristics Taboo Search and Particle Swarm Optimization. Besides, we investigate some aspects that must be considered in order to achieve better solutions than those obtained by the original heuristics. The results demonstrate that the algorithms derived from these three hybrid models are more robust than the original algorithms and able to get better results than those found by the single Taboo Search.
Protopopescu, V.; D'Helon, C.; Barhen, J.
2003-06-01
A constant-time solution of the continuous global optimization problem (GOP) is obtained by using an ensemble algorithm. We show that under certain assumptions, the solution can be guaranteed by mapping the GOP onto a discrete unsorted search problem, whereupon Brüschweiler's ensemble search algorithm is applied. For adequate sensitivities of the measurement technique, the query complexity of the ensemble search algorithm depends linearly on the size of the function's domain. Advantages and limitations of an eventual NMR implementation are discussed.
IESIP - AN IMPROVED EXPLORATORY SEARCH TECHNIQUE FOR PURE INTEGER LINEAR PROGRAMMING PROBLEMS
Fogle, F. R.
1994-01-01
IESIP, an Improved Exploratory Search Technique for Pure Integer Linear Programming Problems, addresses the problem of optimizing an objective function of one or more variables subject to a set of confining functions or constraints by a method called discrete optimization or integer programming. Integer programming is based on a specific form of the general linear programming problem in which all variables in the objective function and all variables in the constraints are integers. While more difficult, integer programming is required for accuracy when modeling systems with small numbers of components such as the distribution of goods, machine scheduling, and production scheduling. IESIP establishes a new methodology for solving pure integer programming problems by utilizing a modified version of the univariate exploratory move developed by Robert Hooke and T.A. Jeeves. IESIP also takes some of its technique from the greedy procedure and the idea of unit neighborhoods. A rounding scheme uses the continuous solution found by traditional methods (simplex or other suitable technique) and creates a feasible integer starting point. The Hook and Jeeves exploratory search is modified to accommodate integers and constraints and is then employed to determine an optimal integer solution from the feasible starting solution. The user-friendly IESIP allows for rapid solution of problems up to 10 variables in size (limited by DOS allocation). Sample problems compare IESIP solutions with the traditional branch-and-bound approach. IESIP is written in Borland's TURBO Pascal for IBM PC series computers and compatibles running DOS. Source code and an executable are provided. The main memory requirement for execution is 25K. This program is available on a 5.25 inch 360K MS DOS format diskette. IESIP was developed in 1990. IBM is a trademark of International Business Machines. TURBO Pascal is registered by Borland International.
[Development of domain specific search engines].
Takai, T; Tokunaga, M; Maeda, K; Kaminuma, T
2000-01-01
As cyber space exploding in a pace that nobody has ever imagined, it becomes very important to search cyber space efficiently and effectively. One solution to this problem is search engines. Already a lot of commercial search engines have been put on the market. However these search engines respond with such cumbersome results that domain specific experts can not tolerate. Using a dedicate hardware and a commercial software called OpenText, we have tried to develop several domain specific search engines. These engines are for our institute's Web contents, drugs, chemical safety, endocrine disruptors, and emergent response for chemical hazard. These engines have been on our Web site for testing.
Sharing problem gamblers’ experiences: a text analysis of gambling stories via online forum
Directory of Open Access Journals (Sweden)
Andrea Caputo
2015-05-01
Full Text Available The present study explored some common thematic domains which characterised problem gambling experiences of adult Italian participants with the aim of understanding motivations and expectations of problem gamblers and thus promoting better psychological interventions. Emotional Text Analysis was performed on 24 problem gambling stories collected via online forum in order to detect the main themes (cluster analysis and latent factors (correspondence analysis emerging in gamblers’ narratives. Five themes emerged which respectively refer to guilt (16.15%, obsession (27.60%, disease (30.77%, risk taking (15.89% and emotion regulation (4.17%. In addition, four synthetic dimensions were detected which consent to account the variability of problem gambling experience based on: struggle against compulsion (F1, ambivalent acceptance of gambling (F2, interpersonal detachment (F3 and illusion of control (F4. From the emotional experience shaping the problem gamblers’ narratives, this research study allows the identification of some factors which can contribute to quality research on problem gambling and which can provide some useful suggestion for treatment.
A Problem-Reduction Evolutionary Algorithm for Solving the Capacitated Vehicle Routing Problem
Directory of Open Access Journals (Sweden)
Wanfeng Liu
2015-01-01
Full Text Available Assessment of the components of a solution helps provide useful information for an optimization problem. This paper presents a new population-based problem-reduction evolutionary algorithm (PREA based on the solution components assessment. An individual solution is regarded as being constructed by basic elements, and the concept of acceptability is introduced to evaluate them. The PREA consists of a searching phase and an evaluation phase. The acceptability of basic elements is calculated in the evaluation phase and passed to the searching phase. In the searching phase, for each individual solution, the original optimization problem is reduced to a new smaller-size problem. With the evolution of the algorithm, the number of common basic elements in the population increases until all individual solutions are exactly the same which is supposed to be the near-optimal solution of the optimization problem. The new algorithm is applied to a large variety of capacitated vehicle routing problems (CVRP with customers up to nearly 500. Experimental results show that the proposed algorithm has the advantages of fast convergence and robustness in solution quality over the comparative algorithms.
Generalised Adaptive Harmony Search: A Comparative Analysis of Modern Harmony Search
Directory of Open Access Journals (Sweden)
Jaco Fourie
2013-01-01
Full Text Available Harmony search (HS was introduced in 2001 as a heuristic population-based optimisation algorithm. Since then HS has become a popular alternative to other heuristic algorithms like simulated annealing and particle swarm optimisation. However, some flaws, like the need for parameter tuning, were identified and have been a topic of study for much research over the last 10 years. Many variants of HS were developed to address some of these flaws, and most of them have made substantial improvements. In this paper we compare the performance of three recent HS variants: exploratory harmony search, self-adaptive harmony search, and dynamic local-best harmony search. We compare the accuracy of these algorithms, using a set of well-known optimisation benchmark functions that include both unimodal and multimodal problems. Observations from this comparison led us to design a novel hybrid that combines the best attributes of these modern variants into a single optimiser called generalised adaptive harmony search.
DEFF Research Database (Denmark)
Muller, Laurent Flindt
2009-01-01
We present an application of an Adaptive Large Neighborhood Search (ALNS) algorithm to the Resource-constrained Project Scheduling Problem (RCPSP). The ALNS framework was first proposed by Pisinger and Røpke [19] and can be described as a large neighborhood search algorithm with an adaptive layer......, where a set of destroy/repair neighborhoods compete to modify the current solution in each iteration of the algorithm. Experiments are performed on the wellknown J30, J60 and J120 benchmark instances, which show that the proposed algorithm is competitive and confirms the strength of the ALNS framework...
Generalized Pattern Search methods for a class of nonsmooth optimization problems with structure
Bogani, C.; Gasparo, M. G.; Papini, A.
2009-07-01
We propose a Generalized Pattern Search (GPS) method to solve a class of nonsmooth minimization problems, where the set of nondifferentiability is included in the union of known hyperplanes and, therefore, is highly structured. Both unconstrained and linearly constrained problems are considered. At each iteration the set of poll directions is enforced to conform to the geometry of both the nondifferentiability set and the boundary of the feasible region, near the current iterate. This is the key issue to guarantee the convergence of certain subsequences of iterates to points which satisfy first-order optimality conditions. Numerical experiments on some classical problems validate the method.
Hemmelmayr, Vera C.; Cordeau, Jean-François; Crainic, Teodor Gabriel
2012-01-01
In this paper, we propose an adaptive large neighborhood search heuristic for the Two-Echelon Vehicle Routing Problem (2E-VRP) and the Location Routing Problem (LRP). The 2E-VRP arises in two-level transportation systems such as those encountered in the context of city logistics. In such systems, freight arrives at a major terminal and is shipped through intermediate satellite facilities to the final customers. The LRP can be seen as a special case of the 2E-VRP in which vehicle routing is performed only at the second level. We have developed new neighborhood search operators by exploiting the structure of the two problem classes considered and have also adapted existing operators from the literature. The operators are used in a hierarchical scheme reflecting the multi-level nature of the problem. Computational experiments conducted on several sets of instances from the literature show that our algorithm outperforms existing solution methods for the 2E-VRP and achieves excellent results on the LRP. PMID:23483764
Gao, Kaizhou; Wang, Ling; Luo, Jianping; Jiang, Hua; Sadollah, Ali; Pan, Quanke
2018-06-01
In this article, scheduling and rescheduling problems with increasing processing time and new job insertion are studied for reprocessing problems in the remanufacturing process. To handle the unpredictability of reprocessing time, an experience-based strategy is used. Rescheduling strategies are applied for considering the effect of increasing reprocessing time and the new subassembly insertion. To optimize the scheduling and rescheduling objective, a discrete harmony search (DHS) algorithm is proposed. To speed up the convergence rate, a local search method is designed. The DHS is applied to two real-life cases for minimizing the maximum completion time and the mean of earliness and tardiness (E/T). These two objectives are also considered together as a bi-objective problem. Computational optimization results and comparisons show that the proposed DHS is able to solve the scheduling and rescheduling problems effectively and productively. Using the proposed approach, satisfactory optimization results can be achieved for scheduling and rescheduling on a real-life shop floor.
Hemmelmayr, Vera C; Cordeau, Jean-François; Crainic, Teodor Gabriel
2012-12-01
In this paper, we propose an adaptive large neighborhood search heuristic for the Two-Echelon Vehicle Routing Problem (2E-VRP) and the Location Routing Problem (LRP). The 2E-VRP arises in two-level transportation systems such as those encountered in the context of city logistics. In such systems, freight arrives at a major terminal and is shipped through intermediate satellite facilities to the final customers. The LRP can be seen as a special case of the 2E-VRP in which vehicle routing is performed only at the second level. We have developed new neighborhood search operators by exploiting the structure of the two problem classes considered and have also adapted existing operators from the literature. The operators are used in a hierarchical scheme reflecting the multi-level nature of the problem. Computational experiments conducted on several sets of instances from the literature show that our algorithm outperforms existing solution methods for the 2E-VRP and achieves excellent results on the LRP.
Björn, Piia Maria; Aunola, Kaisa; Nurmi, Jari-Erik
2016-01-01
This longitudinal study aimed to investigate the extent to which primary school text comprehension predicts mathematical word problem-solving skills in secondary school among Finnish students. The participants were 224 fourth graders (9-10 years old at the baseline). The children's text-reading fluency, text comprehension and basic calculation…
Does despotic behavior or food search explain the occurrence of problem brown bears in Europe?
Elfström, Marcus; Zedrosser, Andreas; Jerina, Klemen; Støen, Ole-Gunnar; Kindberg, Jonas; Budic, Lara; Jonozovič, Marko; Swenson, Jon E
2014-01-01
Bears foraging near human developments are often presumed to be responding to food shortage, but this explanation ignores social factors, in particular despotism in bears. We analyzed the age distribution and body condition index (BCI) of shot brown bears in relation to densities of bears and people, and whether the shot bears were killed by managers (i.e., problem bears; n = 149), in self-defense (n = 51), or were hunter-killed nonproblem bears (n = 1,896) during 1990–2010. We compared patterns between areas with (Slovenia) and without supplemental feeding (Sweden) of bears relative to 2 hypotheses. The food-search/food-competition hypothesis predicts that problem bears should have a higher BCI (e.g., exploiting easily accessible and/or nutritious human-derived foods) or lower BCI (e.g., because of food shortage) than nonproblem bears, that BCI and human density should have a positive correlation, and problem bear occurrence and seasonal mean BCI of nonproblem bears should have a negative correlation (i.e., more problem bears during years of low food availability). Food competition among bears additionally predicts an inverse relationship between BCI and bear density. The safety-search/naivety hypothesis (i.e., avoiding other bears or lack of human experience) predicts no relationship between BCI and human density, provided no dietary differences due to spatiotemporal habitat use among bears, no relationship between problem bear occurrence and seasonal mean BCI of nonproblem bears, and does not necessarily predict a difference between BCI for problem/nonproblem bears. If food competition or predation avoidance explained bear occurrence near settlements, we predicted younger problem than nonproblem bears and a negative correlation between age and human density. However, if only food search explained bear occurrence near settlements, we predicted no relation between age and problem or nonproblem bear status, or between age and human density. We found
The database search problem: a question of rational decision making.
Gittelson, S; Biedermann, A; Bozza, S; Taroni, F
2012-10-10
This paper applies probability and decision theory in the graphical interface of an influence diagram to study the formal requirements of rationality which justify the individualization of a person found through a database search. The decision-theoretic part of the analysis studies the parameters that a rational decision maker would use to individualize the selected person. The modeling part (in the form of an influence diagram) clarifies the relationships between this decision and the ingredients that make up the database search problem, i.e., the results of the database search and the different pairs of propositions describing whether an individual is at the source of the crime stain. These analyses evaluate the desirability associated with the decision of 'individualizing' (and 'not individualizing'). They point out that this decision is a function of (i) the probability that the individual in question is, in fact, at the source of the crime stain (i.e., the state of nature), and (ii) the decision maker's preferences among the possible consequences of the decision (i.e., the decision maker's loss function). We discuss the relevance and argumentative implications of these insights with respect to recent comments in specialized literature, which suggest points of view that are opposed to the results of our study. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Tabu search for the redundancy allocation problem of homogenous series-parallel multi-state systems
International Nuclear Information System (INIS)
Ouzineb, Mohamed; Nourelfath, Mustapha; Gendreau, Michel
2008-01-01
This paper develops an efficient tabu search (TS) heuristic to solve the redundancy allocation problem for multi-state series-parallel systems. The system has a range of performance levels from perfect functioning to complete failure. Identical redundant elements are included in order to achieve a desirable level of availability. The elements of the system are characterized by their cost, performance and availability. These elements are chosen from a list of products available in the market. System availability is defined as the ability to satisfy consumer demand, which is represented as a piecewise cumulative load curve. A universal generating function technique is applied to evaluate system availability. The proposed TS heuristic determines the minimal cost system configuration under availability constraints. An originality of our approach is that it proceeds by dividing the search space into a set of disjoint subsets, and then by applying TS to each subset. The design problem, solved in this study, has been previously analyzed using genetic algorithms (GAs). Numerical results for the test problems from previous research are reported, and larger test problems are randomly generated. Comparisons show that the proposed TS out-performs GA solutions, in terms of both the solution quality and the execution time
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Sahbi Marrouchi
2018-02-01
Full Text Available Solving the Unit Commitment problem (UCP optimizes the combination of production units operations and determines the appropriate operational scheduling of each production units to satisfy the expected consumption which varies from one day to one month. Besides, each production unit is conducted to constraints that render this problem complex, combinatorial and nonlinear. In this paper, we proposed a new strategy based on the combination three optimization methods: Tabu search, Particle swarm optimization and Lagrangian relaxation methods in order to develop a proper unit commitment scheduling of the production units while reducing the production cost during a definite period. The proposed strategy has been implemented on a the IEEE 9 bus test system containing 3 production unit and the results were promising compared to strategies based on meta-heuristic and deterministic methods.
Truong, Long T; De Gruyter, Chris; Nguyen, Hang T T
2017-08-18
The objective of this study was to investigate the prevalence of calling, texting, and searching for information while riding a motorcycle among university students and the influences of sociodemographic characteristics, social norms, and risk perceptions on these behaviors. Students at 2 university campuses in Hanoi and Ho Chi Minh City, the 2 largest cities in Vietnam, were invited to participate in an anonymous online survey. Data collection was conducted during March and May 2016. There were 741 respondents, of whom nearly 90% of students (665) were motorcycle riders. Overall prevalence of mobile phone use while riding is 80.9% (95% confidence interval [CI], 77.9-83.9%) with calling having a higher level of prevalence than texting or searching for information while riding: 74% (95% CI, 70.7-77.3%) vs. 51.7% (95% CI, 47.9-55.5%) and 49.9% (95% CI, 46.1-53.7%), respectively. Random parameter ordered probit modeling results indicate that mobile phone use while riding is associated with gender, motorcycle license duration, perceived crash risk, perceived risk of mobile phone snatching, and perceptions of friends' mobile phone use while riding. Mobile phone use while riding a motorcycle is highly prevalent among university students. Educational programs should focus on the crash and economic risk of all types of mobile phone use while riding, including calling, texting, and searching for information. In addition, they should consider targeting the influence of social norms and peers on mobile phone use while riding.
Constraint Programming based Local Search for the Vehicle Routing Problem with Time Windows
Sala Reixach, Joan
2012-01-01
El projecte es centra en el "Vehicle Routing Problem with Time Windows". Explora i testeja un mètode basat en una formulació del problema en termes de programació de restriccions. Implementa un mètode de cerca local amb la capacitat de fer grans moviments anomenat "Large Neighbourhood Search".
The Development of a Combined Search for a Heterogeneous Chemistry Database
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Lulu Jiang
2015-05-01
Full Text Available A combined search, which joins a slow molecule structure search with a fast compound property search, results in more accurate search results and has been applied in several chemistry databases. However, the problems of search speed differences and combining the two separate search results are two major challenges. In this paper, two kinds of search strategies, synchronous search and asynchronous search, are proposed to solve these problems in the heterogeneous structure database and the property database found in ChemDB, a chemistry database owned by the Institute of Process Engineering, CAS. Their advantages and disadvantages under different conditions are discussed in detail. Furthermore, we applied these two searches to ChemDB and used them to screen for potential molecules that can work as CO2 absorbents. The results reveal that this combined search discovers reasonable target molecules within an acceptable time frame.
Problem solving stages in the five square problem
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Anna eFedor
2015-08-01
Full Text Available According to the restructuring hypothesis, insight problem solving typically progresses through consecutive stages of search, impasse, insight and search again for someone, who solves the task. The order of these stages was determined through self-reports of problem solvers and has never been verified behaviourally. We asked whether individual analysis of problem solving attempts of participants revealed the same order of problem solving stages as defined by the theory and whether their subjective feelings corresponded to the problem solving stages they were in. 101 participants tried to solve the Five-Square problem in an online task, while we recorded the time and trajectory of their stick movements. After the task they were asked about their feelings related to insight and 67 of them also had the possibility of reporting impasse while working on the task. We have found that 49% (19 out of 39 of the solvers and 13% (8 out of 62 of the non-solvers followed the classic four-stage model of insight. The rest of the participants had more complex sequences of problem solving stages, with search and impasse recurring several times. This means that the classic four-stage model must be extended to explain variability on the individual level. We provide a model that can generate all sequences found. Solvers reported insight more often than non-solvers and non-solvers reported impasse more often than solvers, as expected; but participants did not report impasse more often during behaviourally defined impasse stages than during other stages. This shows that impasse reports might be unreliable indicators of impasse. Our study highlights the importance of individual analysis of problem solving behaviour to verify insight theory.
Kombinasi Firefly Algorithm-Tabu Search untuk Penyelesaian Traveling Salesman Problem
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Riyan Naufal Hay's
2017-07-01
Full Text Available Traveling Salesman Problem (TSP adalah masalah optimasi kombinatorial klasik dan memiliki peran dalam perencanaan, penjadwalan, dan pencarian pada bidang rekayasa dan pengetahuan (Dong, 2012. TSP juga merupakan objek yang baik untuk menguji kinerja metode optimasi, beberapa metode seperti Cooperative Genetic Ant System (CGAS (Dong, 2012, Parallelized Genetic Ant Colony System (PGAS Particle Swarm Optimization and Ant Colony Optimization Algorithms (PSO–ACO (Elloumi, 2014, dan Ant Colony Hyper-Heuristics (ACO HH (Aziz, 2015 telah dikembangkan untuk memecahkan TSP. Sehingga, pada penelitian ini diimplementasikan kombinasi metode baru untuk meningkatkan akurasi penyelesaian TSP. Firefly Algorithm (FA merupakan salah satu algoritma yang dapat digunakan untuk memecahkan masalah optimasi kombinatorial (Layeb, 2014. FA merupakan algoritma yang berpotensi kuat dalam memecahkan kasus optimasi dibanding algoritma yang ada termasuk Particle Swarm Optimization (Yang, 2010. Namun, FA memiliki kekurangan dalam memecahkan masalah optimasi dengan skala besar (Baykasoğlu dan Ozsoy, 2014. Tabu Search (TS merupakan metode optimasi yang terbukti efektif untuk memecahkan masalah optimasi dengan skala besar (Pedro, 2013. Pada penelitian ini, TS akan diterapkan pada FA (FATS untuk memecahkan kasus TSP. Hasil FATS akan dibandingkan terhadap penelitian sebelumnya yaitu ACOHH. Perbandingan hasil menunjukan peningkatan akurasi sebesar 0.89% pada dataset Oliver30, 0.14% dataset Eil51, 3.81% dataset Eil76 dan 1.27% dataset KroA100.
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Yunyun Niu
2018-01-01
Full Text Available Outsourcing logistics operation to third-party logistics has attracted more attention in the past several years. However, very few papers analyzed fuel consumption model in the context of outsourcing logistics. This problem involves more complexity than traditional open vehicle routing problem (OVRP, because the calculation of fuel emissions depends on many factors, such as the speed of vehicles, the road angle, the total load, the engine friction, and the engine displacement. Our paper proposed a green open vehicle routing problem (GOVRP model with fuel consumption constraints for outsourcing logistics operations. Moreover, a hybrid tabu search algorithm was presented to deal with this problem. Experiments were conducted on instances based on realistic road data of Beijing, China, considering that outsourcing logistics plays an increasingly important role in China’s freight transportation. Open routes were compared with closed routes through statistical analysis of the cost components. Compared with closed routes, open routes reduce the total cost by 18.5% with the fuel emissions cost down by nearly 29.1% and the diver cost down by 13.8%. The effect of different vehicle types was also studied. Over all the 60- and 120-node instances, the mean total cost by using the light-duty vehicles is the lowest.
CLASSIFICATION OF TRAFFIC RELATED SHORT TEXTS TO ANALYSE ROAD PROBLEMS IN URBAN AREAS
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A. M. M. Saldana-Perez
2017-09-01
Full Text Available The Volunteer Geographic Information (VGI can be used to understand the urban dynamics. In the classification of traffic related short texts to analyze road problems in urban areas, a VGI data analysis is done over a social media’s publications, in order to classify traffic events at big cities that modify the movement of vehicles and people through the roads, such as car accidents, traffic and closures. The classification of traffic events described in short texts is done by applying a supervised machine learning algorithm. In the approach users are considered as sensors which describe their surroundings and provide their geographic position at the social network. The posts are treated by a text mining process and classified into five groups. Finally, the classified events are grouped in a data corpus and geo-visualized in the study area, to detect the places with more vehicular problems.
Cuckoo search via Levy flights applied to uncapacitated facility location problem
Mesa, Armacheska; Castromayor, Kris; Garillos-Manliguez, Cinmayii; Calag, Vicente
2017-11-01
Facility location problem (FLP) is a mathematical way to optimally locate facilities within a set of candidates to satisfy the requirements of a given set of clients. This study addressed the uncapacitated FLP as it assures that the capacity of every selected facility is finite. Thus, even if the demand is not known, which often is the case, in reality, organizations may still be able to take strategic decisions such as locating the facilities. There are different approaches relevant to the uncapacitated FLP. Here, the cuckoo search via Lévy flight (CS-LF) was used to solve the problem. Though hybrid methods produce better results, this study employed CS-LF to determine first its potential in finding solutions for the problem, particularly when applied to a real-world problem. The method was applied to the data set obtained from a department store in Davao City, Philippines. Results showed that applying CS-LF yielded better facility locations compared to particle swarm optimization and other existing algorithms. Although these results showed that CS-LF is a promising method to solve this particular problem, further studies on other FLP are recommended to establish a strong foundation of the capability of CS-LF in solving FLP.
Improved Degree Search Algorithms in Unstructured P2P Networks
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Guole Liu
2012-01-01
Full Text Available Searching and retrieving the demanded correct information is one important problem in networks; especially, designing an efficient search algorithm is a key challenge in unstructured peer-to-peer (P2P networks. Breadth-first search (BFS and depth-first search (DFS are the current two typical search methods. BFS-based algorithms show the perfect performance in the aspect of search success rate of network resources, while bringing the huge search messages. On the contrary, DFS-based algorithms reduce the search message quantity and also cause the dropping of search success ratio. To address the problem that only one of performances is excellent, we propose two memory function degree search algorithms: memory function maximum degree algorithm (MD and memory function preference degree algorithm (PD. We study their performance including the search success rate and the search message quantity in different networks, which are scale-free networks, random graph networks, and small-world networks. Simulations show that the two performances are both excellent at the same time, and the performances are improved at least 10 times.
M.J. Huiskes (Mark)
2004-01-01
textabstractIn this paper we focus on a number of issues regarding special structure in the relevance feedback learning problem, most notably the effects of image selection based on partial relevance on the clustering behavior of examples. We propose a simple scheme, aspect-based image search, which
Quan, Zhe; Wu, Lei
2017-09-01
This article investigates the use of parallel computing for solving the disjunctively constrained knapsack problem. The proposed parallel computing model can be viewed as a cooperative algorithm based on a multi-neighbourhood search. The cooperation system is composed of a team manager and a crowd of team members. The team members aim at applying their own search strategies to explore the solution space. The team manager collects the solutions from the members and shares the best one with them. The performance of the proposed method is evaluated on a group of benchmark data sets. The results obtained are compared to those reached by the best methods from the literature. The results show that the proposed method is able to provide the best solutions in most cases. In order to highlight the robustness of the proposed parallel computing model, a new set of large-scale instances is introduced. Encouraging results have been obtained.
Large neighborhood search for the double traveling salesman problem with multiple stacks
Energy Technology Data Exchange (ETDEWEB)
Bent, Russell W [Los Alamos National Laboratory; Van Hentenryck, Pascal [BROWN UNIV
2009-01-01
This paper considers a complex real-life short-haul/long haul pickup and delivery application. The problem can be modeled as double traveling salesman problem (TSP) in which the pickups and the deliveries happen in the first and second TSPs respectively. Moreover, the application features multiple stacks in which the items must be stored and the pickups and deliveries must take place in reserve (LIFO) order for each stack. The goal is to minimize the total travel time satisfying these constraints. This paper presents a large neighborhood search (LNS) algorithm which improves the best-known results on 65% of the available instances and is always within 2% of the best-known solutions.
Sequence Comparison: Close and Open problems
Lenzini, Gabriele; Cerrai, P.; Freguglia, P.
Comparing sequences is a very important activity both in computer science and in a many other areas as well. For example thank to text editors, everyone knows the particular instance of a sequence comparison problem knonw as ``string mathcing problem''. It consists in searching a given work
PubMed-EX: a web browser extension to enhance PubMed search with text mining features.
Tsai, Richard Tzong-Han; Dai, Hong-Jie; Lai, Po-Ting; Huang, Chi-Hsin
2009-11-15
PubMed-EX is a browser extension that marks up PubMed search results with additional text-mining information. PubMed-EX's page mark-up, which includes section categorization and gene/disease and relation mark-up, can help researchers to quickly focus on key terms and provide additional information on them. All text processing is performed server-side, freeing up user resources. PubMed-EX is freely available at http://bws.iis.sinica.edu.tw/PubMed-EX and http://iisr.cse.yzu.edu.tw:8000/PubMed-EX/.
An Enhanced Differential Evolution with Elite Chaotic Local Search
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Zhaolu Guo
2015-01-01
Full Text Available Differential evolution (DE is a simple yet efficient evolutionary algorithm for real-world engineering problems. However, its search ability should be further enhanced to obtain better solutions when DE is applied to solve complex optimization problems. This paper presents an enhanced differential evolution with elite chaotic local search (DEECL. In DEECL, it utilizes a chaotic search strategy based on the heuristic information from the elite individuals to promote the exploitation power. Moreover, DEECL employs a simple and effective parameter adaptation mechanism to enhance the robustness. Experiments are conducted on a set of classical test functions. The experimental results show that DEECL is very competitive on the majority of the test functions.
Harmony Search for Balancing Two-sided Assembly Lines
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Hindriyanto Dwi Purnomo
2012-01-01
Full Text Available Two-sided assembly lines balancing problems are important problem for large-sized products such as cars and buses, in which, tasks operations can be performed in the two sides of the line. In this paper, Harmony Search algorithm is proposed to solve two-sided assembly lines balancing problems type-I (TALBP-I. The proposed method adopts the COMSOAL heuristic and specific features of TALBP in the Harmony operators – the harmony memory consideration, random selection and pitch adjustment – in order to maintain the local and global search. The proposed method is evaluated based on 6 benchmark problems that are commonly used in TALBP. The experiment results show that the proposed method work well and produces better solution than the heuristic method and genetic algorithm.
Iterated local search algorithm for solving the orienteering problem with soft time windows.
Aghezzaf, Brahim; Fahim, Hassan El
2016-01-01
In this paper we study the orienteering problem with time windows (OPTW) and the impact of relaxing the time windows on the profit collected by the vehicle. The way of relaxing time windows adopted in the orienteering problem with soft time windows (OPSTW) that we study in this research is a late service relaxation that allows linearly penalized late services to customers. We solve this problem heuristically by considering a hybrid iterated local search. The results of the computational study show that the proposed approach is able to achieve promising solutions on the OPTW test instances available in the literature, one new best solution is found. On the newly generated test instances of the OPSTW, the results show that the profit collected by the OPSTW is better than the profit collected by the OPTW.
Classification of Traffic Related Short Texts to Analyse Road Problems in Urban Areas
Saldana-Perez, A. M. M.; Moreno-Ibarra, M.; Tores-Ruiz, M.
2017-09-01
The Volunteer Geographic Information (VGI) can be used to understand the urban dynamics. In the classification of traffic related short texts to analyze road problems in urban areas, a VGI data analysis is done over a social media's publications, in order to classify traffic events at big cities that modify the movement of vehicles and people through the roads, such as car accidents, traffic and closures. The classification of traffic events described in short texts is done by applying a supervised machine learning algorithm. In the approach users are considered as sensors which describe their surroundings and provide their geographic position at the social network. The posts are treated by a text mining process and classified into five groups. Finally, the classified events are grouped in a data corpus and geo-visualized in the study area, to detect the places with more vehicular problems.
An opposition-based harmony search algorithm for engineering optimization problems
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Abhik Banerjee
2014-03-01
Full Text Available Harmony search (HS is a derivative-free real parameter optimization algorithm. It draws inspiration from the musical improvisation process of searching for a perfect state of harmony. The proposed opposition-based HS (OHS of the present work employs opposition-based learning for harmony memory initialization and also for generation jumping. The concept of opposite number is utilized in OHS to improve the convergence rate of the HS algorithm. The potential of the proposed algorithm is assessed by means of an extensive comparative study of the numerical results on sixteen benchmark test functions. Additionally, the effectiveness of the proposed algorithm is tested for reactive power compensation of an autonomous power system. For real-time reactive power compensation of the studied model, Takagi Sugeno fuzzy logic (TSFL is employed. Time-domain simulation reveals that the proposed OHS-TSFL yields on-line, off-nominal model parameters, resulting in real-time incremental change in terminal voltage response profile.
A NNIA Scheme for Timetabling Problems
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Yu Lei
2017-01-01
Full Text Available This paper presents a memetic multiobjective optimization algorithm based on NNIA for examination timetabling problems. In this paper, the examination timetabling problem is considered as a two-objective optimization problem while it is modeled as a single-objective optimization problem generally. Within the NNIA framework, the special crossover operator is utilized to search in the solution space; two local search techniques are employed to optimize these two objectives and a diversity-keeping strategy which consists of an elitism group operator and an extension optimization operator to ensure a sufficient number of solutions in the pareto front. The proposed algorithm was tested on the most widely used uncapacitated Carter benchmarks. Experimental results prove that the proposed algorithm is a competitive algorithm.
Search for H $\\to$ b$\\bar{\\text{b}}$ in association with a single top quark at CMS
Mueller, Denise
2017-01-01
A search for the production of a Higgs boson in association with a single top quark (tH) is performed using the decay H $\\to$ b$\\bar{\\text{b}}$. This Higgs boson production mode is sensitive to the coupling modifiers of the Higgs boson to top quarks ($\\kappa_{\\text{t}}$) and to weak gauge bosons ($\\kappa_{\\text{V}}$) and thus can be used to lift the degeneracy regarding the sign of the top quark Yukawa coupling. The 2015 pp collisions data at a center-of-mass energy of 13 TeV are analyzed. Boosted decision trees are used to reconstruct and classify the events. Upper limits on the tH production cross section are determined at 51 different points in the $\\kappa_{\\text{t}}-\\kappa_{\\text{V}}$ plane.
Heuristic Search Theory and Applications
Edelkamp, Stefan
2011-01-01
Search has been vital to artificial intelligence from the very beginning as a core technique in problem solving. The authors present a thorough overview of heuristic search with a balance of discussion between theoretical analysis and efficient implementation and application to real-world problems. Current developments in search such as pattern databases and search with efficient use of external memory and parallel processing units on main boards and graphics cards are detailed. Heuristic search as a problem solving tool is demonstrated in applications for puzzle solving, game playing, constra
International Nuclear Information System (INIS)
Shlesinger, Michael F
2009-01-01
There are a wide variety of searching problems from molecules seeking receptor sites to predators seeking prey. The optimal search strategy can depend on constraints on time, energy, supplies or other variables. We discuss a number of cases and especially remark on the usefulness of Levy walk search patterns when the targets of the search are scarce.
Generalizing Backtrack-Free Search: A Framework for Search-Free Constraint Satisfaction
Jonsson, Ari K.; Frank, Jeremy
2000-01-01
Tractable classes of constraint satisfaction problems are of great importance in artificial intelligence. Identifying and taking advantage of such classes can significantly speed up constraint problem solving. In addition, tractable classes are utilized in applications where strict worst-case performance guarantees are required, such as constraint-based plan execution. In this work, we present a formal framework for search-free (backtrack-free) constraint satisfaction. The framework is based on general procedures, rather than specific propagation techniques, and thus generalizes existing techniques in this area. We also relate search-free problem solving to the notion of decision sets and use the result to provide a constructive criterion that is sufficient to guarantee search-free problem solving.
A Prefiltered Cuckoo Search Algorithm with Geometric Operators for Solving Sudoku Problems
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Ricardo Soto
2014-01-01
Full Text Available The Sudoku is a famous logic-placement game, originally popularized in Japan and today widely employed as pastime and as testbed for search algorithms. The classic Sudoku consists in filling a 9×9 grid, divided into nine 3×3 regions, so that each column, row, and region contains different digits from 1 to 9. This game is known to be NP-complete, with existing various complete and incomplete search algorithms able to solve different instances of it. In this paper, we present a new cuckoo search algorithm for solving Sudoku puzzles combining prefiltering phases and geometric operations. The geometric operators allow one to correctly move toward promising regions of the combinatorial space, while the prefiltering phases are able to previously delete from domains the values that do not conduct to any feasible solution. This integration leads to a more efficient domain filtering and as a consequence to a faster solving process. We illustrate encouraging experimental results where our approach noticeably competes with the best approximate methods reported in the literature.
A Dynamic Methodology for Improving the Search Experience
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Marcia D. Kerchner
2006-06-01
Full Text Available In the early years of modern information retrieval, the fundamental way in which we understood and evaluated search performance was by measuring precision and recall. In recent decades, however, models of evaluation have expanded to incorporate the information-seeking task and the quality of its outcome, as well as the value of the information to the user. We have developed a systems engineering-based methodology for improving the whole search experience. The approach focuses on understanding users’ information-seeking problems, understanding who has the problems, and applying solutions that address these problems. This information is gathered through ongoing analysis of site-usage reports, satisfaction surveys, Help Desk reports, and a working relationship with the business owners.
State-of-the-Art Review on Relevance of Genetic Algorithm to Internet Web Search
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Kehinde Agbele
2012-01-01
Full Text Available People use search engines to find information they desire with the aim that their information needs will be met. Information retrieval (IR is a field that is concerned primarily with the searching and retrieving of information in the documents and also searching the search engine, online databases, and Internet. Genetic algorithms (GAs are robust, efficient, and optimizated methods in a wide area of search problems motivated by Darwin’s principles of natural selection and survival of the fittest. This paper describes information retrieval systems (IRS components. This paper looks at how GAs can be applied in the field of IR and specifically the relevance of genetic algorithms to internet web search. Finally, from the proposals surveyed it turns out that GA is applied to diverse problem fields of internet web search.
Vatutin, Eduard
2017-12-01
The article deals with the problem of analysis of effectiveness of the heuristic methods with limited depth-first search techniques of decision obtaining in the test problem of getting the shortest path in graph. The article briefly describes the group of methods based on the limit of branches number of the combinatorial search tree and limit of analyzed subtree depth used to solve the problem. The methodology of comparing experimental data for the estimation of the quality of solutions based on the performing of computational experiments with samples of graphs with pseudo-random structure and selected vertices and arcs number using the BOINC platform is considered. It also shows description of obtained experimental results which allow to identify the areas of the preferable usage of selected subset of heuristic methods depending on the size of the problem and power of constraints. It is shown that the considered pair of methods is ineffective in the selected problem and significantly inferior to the quality of solutions that are provided by ant colony optimization method and its modification with combinatorial returns.
Directory of Open Access Journals (Sweden)
Mohammed Zia
2018-03-01
Full Text Available The Equality-Generalized Travelling Salesman Problem (E-GTSP, which is an extension of the Travelling Salesman Problem (TSP, is stated as follows: given groups of points within a city, like banks, supermarkets, etc., find a minimum cost Hamiltonian cycle that visits each group exactly once. It can model many real-life combinatorial optimization scenarios more efficiently than TSP. This study presents five spatially driven search-algorithms for possible transformation of E-GTSP to TSP by considering the spatial spread of points in a given urban city. Presented algorithms are tested over 15 different cities, classified by their street-network’s fractal-dimension. Obtained results denote that the R-Search algorithm, which selects the points from each group based on their radial separation with respect to the start–end point, is the best search criterion for any E-GTSP to TSP conversion modelled for a city street network. An 8.8% length error has been reported for this algorithm.
Toward an automaton Constraint for Local Search
Directory of Open Access Journals (Sweden)
Jun He
2009-10-01
Full Text Available We explore the idea of using finite automata to implement new constraints for local search (this is already a successful technique in constraint-based global search. We show how it is possible to maintain incrementally the violations of a constraint and its decision variables from an automaton that describes a ground checker for that constraint. We establish the practicality of our approach idea on real-life personnel rostering problems, and show that it is competitive with the approach of [Pralong, 2007].
Problems encountered in searching for new strains of toxic planktonic cyanobacteria
Energy Technology Data Exchange (ETDEWEB)
Gorham, P.R.; McNicholas, S.; Allen, E.A.D. (Alberta Univ., Edmonton (Canada))
1982-09-01
In 1979 and 1980, four blooms from Lac La Nonne (80 km NW of Edmonton, Alberta) dominated 67 to 95 percent by Aphanizomenon flos-aquae L., were found to be type-c-toxic to mice and agglutinated red blood cells. A search for type-c-toxic strains of Aphanizomenon in this lake was undertaken in 1980 and 1981 by making 128 colony isolates and testing the unialgal cultures obtained from five blooms which varied in composition from 10 to 95 precent Aphanizomenon. The following problems were encountered in this search and in attempts to obtain axenic clones of different species: 1)a high precentage of isolation failures caused by the gradual but complete take-over of most of the Aphanizomenon cultures by a purple-brown species of Pseudanabaena, 2)stasis or lysis caused by pH and/or composition of the medium or the agar, 3)stasis or lysis caused by bacteria in liquid microculture, on agar streaks or in agar pour-plates, 4) autolysis triggered by tensile stress during transfer of trichomes with loop or needle, 5)inability of graded dosages of gamma rays of sodium sulphide selectively to eliminate or reduce numbers of bacteria to a satisfactory level for plating, 6)autolysis and growth inhibition caused by gentle washing to reduce numbers of bacteria for plating, and 7)discovery that haemagglutination is not perfectly correlated with type-c-toxicity. The search produced no type-c toxic strains of Aphanizomenon but two heterogeneous take-over cultures of Pseudanabaena sp. were found that produced violent convulsions when injected intraperitoneally into mice.
Problems encountered in searching for new strains of toxic planktonic syanobacteria
International Nuclear Information System (INIS)
Gorham, P.R.; McNicholas, S.; Allen, E.A.D.
1982-01-01
In 1979 and 1980, four blooms from Lac La Nonne (80 km NW of Edmonton, Alberta) dominated 67 to 95 percent by Aphanizomenon flos-aquae L., were found to be type-c-toxic to mice and agglutinated red blood cells. A search for type-c-toxic strains of Aphanizomenon in this lake was undertaken in 1980 and 1981 by making 128 colony isolates and testing the unialgal cultures obtained from five blooms which varied in composition from 10 to 95 precent Aphanizomenon. The following problems were encountered in this search and in attempts to obtain axenic clones of different species: 1)a high precentage of isolation failures caused by the gradual but complete take-over of most of the Aphanizomenon cultures by a purple-brown species of Pseudanabaena, 2)stasis or lysis caused by pH and/or composition of the medium or the agar, 3)stasis or lysis caused by bacteria in liquid microculture, on agar streaks or in agar pour-plates, 4) autolysis triggered by tensile stress during transfer of trichomes with loop or needle, 5)inability of graded dosages of gamma rays of sodium sulphide selectively to eliminate or reduce numbers of bacteria to a satisfactory level for plating, 6)autolysis and growth inhibition caused by gentle washing to reduce numbers of bacteria for plating, and 7)discovery that haemagglutination is not perfectly correlated with type-c-toxicity. The search produced no type-c toxic strains of Aphanizomenon but two heterogeneous take-over cultures of Pseudanabaena sp. were found that produced violent convulsions when injected intraperitoneally into mice
Search and imperative programming
Apt, Krzysztof; Schaerf, A.
1996-01-01
textabstractWe augment the expressive power of imperative programming in order to make it a more attractive vehicle for problems that involve search.The proposed additions are limited yet powerful and are inspired by the logic programming paradigm.We illustrate their use by presenting solutions to a number of classical problems, including the straight search problem, the knapsack problem, and the 8 queens problem. These solutions are substantially simpler than their counterparts written in th...
Adding Search as a first-class citizen to Hadoop
CERN. Geneva
2014-01-01
Apache Hadoop is enabling organizations to collect larger, more varied data - but after it's collected how will it be found? Your users expect to be able to search for information using simple text based queries -- regardless of data location, size, and complexity. How do they quickly find information that's just been created, or been stored for months or even years? Cloudera Search Senior Software Engineer Wolfgang Hoschek will present a solution to this problem; what architecture is necessary to search HDFS and HBase? How was Apache Solr, Lucene, Flume and MapReduce integrated to allow for Near Real Time and Batch indexing of data? What are the solved problems and what's still to come? Join us for an exciting discussion on this new technology. About the speaker Wolfgang Hoschek is a Software Engineer at Cloudera working on the Hadoop Platform and Cloudera Search team. He is a committer on the Apache Flume and Apache Lucene/Solr projects, a committer on the Kite project, a committer...
A Study on Control System Design Based on ARM Sea Target Search System
Directory of Open Access Journals (Sweden)
Lin Xinwei
2015-01-01
Full Text Available The infrared detector is used for sea target search, which can assist humans in searching suspicious objects at night and under poor visibility conditions, and improving search efficiency. This paper applies for interrupt and stack technology to solve problems of data losses that may be caused by one-to-many multi-byte protocol communication. Meanwhile, this paper implements hardware and software design of the system based on industrial-grade ARM control chip and uC / OS-II embedded operating system. The control system in the sea target search system is an information exchange and control center of the whole system, which solves the problem of controlling over the shooting angle of the infrared detector in the process of target search. After testing, the control system operates stably and reliably, and realizes rotation and control functions of the pan/tilt platform during automatic search, manual search and track.
DEFF Research Database (Denmark)
Wen, Min; Krapper, Emil; Larsen, Jesper
2011-01-01
in their fresh meat supply logistics system. The problem consists of a 1‐week planning horizon, heterogeneous vehicles, and drivers with predefined work regulations. These regulations include, among other things, predefined workdays, fixed starting time, maximum weekly working duration, and a break rule......The world's second largest producer of pork, Danish Crown, also provides a fresh meat supply logistics system within Denmark. This is used by the majority of supermarkets in Denmark. This article addresses an integrated vehicle routing and driver scheduling problem arising at Danish Crown....... The objective is to minimize the total delivery cost that is a weighted sum of two kinds of delivery costs. A multilevel variable neighborhood search heuristic is proposed for the problem. In a preprocessing step, the problem size is reduced through an aggregation procedure. Thereafter, the aggregated weekly...
Efficient heuristics for the Rural Postman Problem
Directory of Open Access Journals (Sweden)
GW Groves
2005-06-01
Full Text Available A local search framework for the (undirected Rural Postman Problem (RPP is presented in this paper. The framework allows local search approaches that have been applied successfully to the well–known Travelling Salesman Problem also to be applied to the RPP. New heuristics for the RPP, based on this framework, are introduced and these are capable of solving significantly larger instances of the RPP than have been reported in the literature. Test results are presented for a number of benchmark RPP instances in a bid to compare efficiency and solution quality against known methods.
A Hybrid Soft Computing Approach for Subset Problems
Directory of Open Access Journals (Sweden)
Broderick Crawford
2013-01-01
Full Text Available Subset problems (set partitioning, packing, and covering are formal models for many practical optimization problems. A set partitioning problem determines how the items in one set (S can be partitioned into smaller subsets. All items in S must be contained in one and only one partition. Related problems are set packing (all items must be contained in zero or one partitions and set covering (all items must be contained in at least one partition. Here, we present a hybrid solver based on ant colony optimization (ACO combined with arc consistency for solving this kind of problems. ACO is a swarm intelligence metaheuristic inspired on ants behavior when they search for food. It allows to solve complex combinatorial problems for which traditional mathematical techniques may fail. By other side, in constraint programming, the solving process of Constraint Satisfaction Problems can dramatically reduce the search space by means of arc consistency enforcing constraint consistencies either prior to or during search. Our hybrid approach was tested with set covering and set partitioning dataset benchmarks. It was observed that the performance of ACO had been improved embedding this filtering technique in its constructive phase.
An Approach to Retrieval of OCR Degraded Text
Directory of Open Access Journals (Sweden)
Yuen-Hsien Tseng
1998-12-01
Full Text Available The major problem with retrieval of OCR text is the unpredictable distortion of characters due to recognition errors. Because users have no ideas of such distortion, the terms they query can hardly match the terms stored in the OCR text exactly. Thus retrieval effectiveness is significantly reduced , especially for low-quality input. To reduce the losses from retrieving such noisy OCR text, a fault-tolerant retrieval strategy based on automatic keyword extraction and fuzzy matching is proposed. In this strategy, terms, correct or not, and their term frequencies are extracted from the noisy text and presented for browsing and selection in response to users' initial queries , With theunderstanding of the real terms stored in the noisy text and of their estimated frequency distributions, users may then choose appropriate terms for a more effective searching, A text retrieval system based on this strategy has been built. Examples to show the effectiveness are demonstrated. Finally, some OCR issues for further enhancingretrieval effectiveness are discussed.
A Framing Link Based Tabu Search Algorithm for Large-Scale Multidepot Vehicle Routing Problems
Directory of Open Access Journals (Sweden)
Xuhao Zhang
2014-01-01
Full Text Available A framing link (FL based tabu search algorithm is proposed in this paper for a large-scale multidepot vehicle routing problem (LSMDVRP. Framing links are generated during continuous great optimization of current solutions and then taken as skeletons so as to improve optimal seeking ability, speed up the process of optimization, and obtain better results. Based on the comparison between pre- and postmutation routes in the current solution, different parts are extracted. In the current optimization period, links involved in the optimal solution are regarded as candidates to the FL base. Multiple optimization periods exist in the whole algorithm, and there are several potential FLs in each period. If the update condition is satisfied, the FL base is updated, new FLs are added into the current route, and the next period starts. Through adjusting the borderline of multidepot sharing area with dynamic parameters, the authors define candidate selection principles for three kinds of customer connections, respectively. Link split and the roulette approach are employed to choose FLs. 18 LSMDVRP instances in three groups are studied and new optimal solution values for nine of them are obtained, with higher computation speed and reliability.
Distributed Cooperative Search Control Method of Multiple UAVs for Moving Target
Directory of Open Access Journals (Sweden)
Chang-jian Ru
2015-01-01
Full Text Available To reduce the impact of uncertainties caused by unknown motion parameters on searching plan of moving targets and improve the efficiency of UAV’s searching, a novel distributed Multi-UAVs cooperative search control method for moving target is proposed in this paper. Based on detection results of onboard sensors, target probability map is updated using Bayesian theory. A Gaussian distribution of target transition probability density function is introduced to calculate prediction probability of moving target existence, and then target probability map can be further updated in real-time. A performance index function combining with target cost, environment cost, and cooperative cost is constructed, and the cooperative searching problem can be transformed into a central optimization problem. To improve computational efficiency, the distributed model predictive control method is presented, and thus the control command of each UAV can be obtained. The simulation results have verified that the proposed method can avoid the blindness of UAV searching better and improve overall efficiency of the team effectively.
Exploring the role of conceptual scaffolding in solving synthesis problems
Directory of Open Access Journals (Sweden)
Lin Ding1,*
2011-10-01
Full Text Available It is well documented that when solving problems experts first search for underlying concepts while students tend to look for equations and previously worked examples. The overwhelming majority of end-of-chapter (EOC problems in most introductory physics textbooks contain only material and examples discussed in a single chapter, rarely requiring a solver to conduct a general search for underlying concepts. Hypothesizing that complete reliance on EOC problems trains students to rely on a nonexpert approach, we designed and implemented “synthesis” problems, each combining two major concepts that are broadly separated in the teaching timeline. To provide students with guided conceptual scaffolding, we encapsulated each synthesis problem into a sequence with two preceding conceptually based multiple-choice questions. Each question contained one of the major concepts covered in the subsequent synthesis problem. Results from a small-scale interview study and two large-scale written tests showed that the scaffolding encouraged students to search for and apply appropriate fundamental principles in solving synthesis problems, and that repeated training using scaffolded synthesis problems also helped students to make cross-topic transfers.
Directory of Open Access Journals (Sweden)
INTAN S. AHMAD
2008-04-01
Full Text Available This work presents the application of a primal-dual interior point method to minimax optimisation problems. The algorithm differs significantly from previous approaches as it involves a novel non-monotone line search procedure, which is based on the use of standard penalty methods as the merit function used for line search. The crucial novel concept is the discretisation of the penalty parameter used over a finite range of orders of magnitude and the provision of a memory list for each such order. An implementation within a logarithmic barrier algorithm for bounds handling is presented with capabilities for large scale application. Case studies presented demonstrate the capabilities of the proposed methodology, which relies on the reformulation of minimax models into standard nonlinear optimisation models. Some previously reported case studies from the open literature have been solved, and with significantly better optimal solutions identified. We believe that the nature of the non-monotone line search scheme allows the search procedure to escape from local minima, hence the encouraging results obtained.
Fuchs, Lynn S; Gilbert, Jennifer K; Fuchs, Douglas; Seethaler, Pamela M; Martin, BrittanyLee N
2018-01-01
This study was designed to deepen insights on whether word-problem (WP) solving is a form of text comprehension (TC) and on the role of language in WPs. A sample of 325 second graders, representing high, average, and low reading and math performance, was assessed on (a) start-of-year TC, WP skill, language, nonlinguistic reasoning, working memory, and foundational skill (word identification, arithmetic) and (b) year-end WP solving, WP-language processing (understanding WP statements, without calculation demands), and calculations. Multivariate, multilevel path analysis, accounting for classroom and school effects, indicated that TC was a significant and comparably strong predictor of all outcomes. Start-of-year language was a significantly stronger predictor of both year-end WP outcomes than of calculations, whereas start-of-year arithmetic was a significantly stronger predictor of calculations than of either WP measure. Implications are discussed in terms of WP solving as a form of TC and a theoretically coordinated approach, focused on language, for addressing TC and WP-solving instruction.
Improved quantum-behaved particle swarm optimization with local search strategy
Directory of Open Access Journals (Sweden)
Maolong Xi
2017-03-01
Full Text Available Quantum-behaved particle swarm optimization, which was motivated by analysis of particle swarm optimization and quantum system, has shown compared performance in finding the optimal solutions for many optimization problems to other evolutionary algorithms. To address the problem of premature, a local search strategy is proposed to improve the performance of quantum-behaved particle swarm optimization. In proposed local search strategy, a super particle is presented which is a collection body of randomly selected particles’ dimension information in the swarm. The selected probability of particles in swarm is different and determined by their fitness values. To minimization problems, the fitness value of one particle is smaller; the selected probability is more and will contribute more information in constructing the super particle. In addition, in order to investigate the influence on algorithm performance with different local search space, four methods of computing the local search radius are applied in local search strategy and propose four variants of local search quantum-behaved particle swarm optimization. Empirical studies on a suite of well-known benchmark functions are undertaken in order to make an overall performance comparison among the proposed methods and other quantum-behaved particle swarm optimization. The simulation results show that the proposed quantum-behaved particle swarm optimization variants have better advantages over the original quantum-behaved particle swarm optimization.
Directory of Open Access Journals (Sweden)
Derwin Suhartono
2012-06-01
Full Text Available The rapid development of information systems generates new needs for indexing and retrieval of various kinds of media. The need for documents in the form of multimedia is increasing currently. Thus, the need to store or retrieve now becomes a primary problem. The multimedia type commonly used is text types, as widely seen as the main option in the search engines like Yahoo, Google or others. Essentially, search does not just want to get results, but also a more efficient process. For the purposes of indexing and retrieval, inverted file is used to provide faster results. However, there will be a problem if the making of an inverted file is related to a large amount of data. This study describes an algorithm called Fast Inversion as the development of base inverted file making method to address the needs related to the amount of data.
Integrating Conflict Driven Clause Learning to Local Search
Directory of Open Access Journals (Sweden)
Gilles Audenard
2009-10-01
Full Text Available This article introduces SatHyS (SAT HYbrid Solver, a novel hybrid approach for propositional satisfiability. It combines local search and conflict driven clause learning (CDCL scheme. Each time the local search part reaches a local minimum, the CDCL is launched. For SAT problems it behaves like a tabu list, whereas for UNSAT ones, the CDCL part tries to focus on minimum unsatisfiable sub-formula (MUS. Experimental results show good performances on many classes of SAT instances from the last SAT competitions.
The Role of Text Mining in Export Control
Energy Technology Data Exchange (ETDEWEB)
Tae, Jae-woong; Son, Choul-woong; Shin, Dong-hoon [Korea Institute of Nuclear Nonproliferation and Control, Daejeon (Korea, Republic of)
2015-10-15
Korean government provides classification services to exporters. It is simple to copy technology such as documents and drawings. Moreover, it is also easy that new technology derived from the existing technology. The diversity of technology makes classification difficult because the boundary between strategic and nonstrategic technology is unclear and ambiguous. Reviewers should consider previous classification cases enough. However, the increase of the classification cases prevent consistent classifications. This made another innovative and effective approaches necessary. IXCRS (Intelligent Export Control Review System) is proposed to coincide with demands. IXCRS consists of and expert system, a semantic searching system, a full text retrieval system, and image retrieval system and a document retrieval system. It is the aim of the present paper to observe the document retrieval system based on text mining and to discuss how to utilize the system. This study has demonstrated how text mining technique can be applied to export control. The document retrieval system supports reviewers to treat previous classification cases effectively. Especially, it is highly probable that similarity data will contribute to specify classification criterion. However, an analysis of the system showed a number of problems that remain to be explored such as a multilanguage problem and an inclusion relationship problem. Further research should be directed to solve problems and to apply more data mining techniques so that the system should be used as one of useful tools for export control.
The Role of Text Mining in Export Control
International Nuclear Information System (INIS)
Tae, Jae-woong; Son, Choul-woong; Shin, Dong-hoon
2015-01-01
Korean government provides classification services to exporters. It is simple to copy technology such as documents and drawings. Moreover, it is also easy that new technology derived from the existing technology. The diversity of technology makes classification difficult because the boundary between strategic and nonstrategic technology is unclear and ambiguous. Reviewers should consider previous classification cases enough. However, the increase of the classification cases prevent consistent classifications. This made another innovative and effective approaches necessary. IXCRS (Intelligent Export Control Review System) is proposed to coincide with demands. IXCRS consists of and expert system, a semantic searching system, a full text retrieval system, and image retrieval system and a document retrieval system. It is the aim of the present paper to observe the document retrieval system based on text mining and to discuss how to utilize the system. This study has demonstrated how text mining technique can be applied to export control. The document retrieval system supports reviewers to treat previous classification cases effectively. Especially, it is highly probable that similarity data will contribute to specify classification criterion. However, an analysis of the system showed a number of problems that remain to be explored such as a multilanguage problem and an inclusion relationship problem. Further research should be directed to solve problems and to apply more data mining techniques so that the system should be used as one of useful tools for export control
Binary Cockroach Swarm Optimization for Combinatorial Optimization Problem
Directory of Open Access Journals (Sweden)
Ibidun Christiana Obagbuwa
2016-09-01
Full Text Available The Cockroach Swarm Optimization (CSO algorithm is inspired by cockroach social behavior. It is a simple and efficient meta-heuristic algorithm and has been applied to solve global optimization problems successfully. The original CSO algorithm and its variants operate mainly in continuous search space and cannot solve binary-coded optimization problems directly. Many optimization problems have their decision variables in binary. Binary Cockroach Swarm Optimization (BCSO is proposed in this paper to tackle such problems and was evaluated on the popular Traveling Salesman Problem (TSP, which is considered to be an NP-hard Combinatorial Optimization Problem (COP. A transfer function was employed to map a continuous search space CSO to binary search space. The performance of the proposed algorithm was tested firstly on benchmark functions through simulation studies and compared with the performance of existing binary particle swarm optimization and continuous space versions of CSO. The proposed BCSO was adapted to TSP and applied to a set of benchmark instances of symmetric TSP from the TSP library. The results of the proposed Binary Cockroach Swarm Optimization (BCSO algorithm on TSP were compared to other meta-heuristic algorithms.
The ATLAS collaboration
2018-01-01
This note presents the first collider search for light scalar particles that could contribute to the accelerating expansion of the observable universe. The results are based on a re-interpretation of a search for top super-partners using the $t\\bar{t}+E_{T}^{\\text{miss}}$ signature and a search for dark matter using the mono-jet signature. The analysis uses a dataset of LHC $pp$ collision events collected with the ATLAS detector at $\\sqrt{s}=13$ TeV corresponding to an integrated luminosity of 36.1~fb$^{-1}$. No significant excess over the predicted background is observed. The search allows to set the most stringent constraints on the suppression scale of conformal and disformal couplings of dark energy to standard model matter in the context of an effective field theory of dark energy.
All roads lead to Rome - New search methods for the optimal triangulation problem
Czech Academy of Sciences Publication Activity Database
Ottosen, T. J.; Vomlel, Jiří
2012-01-01
Roč. 53, č. 9 (2012), s. 1350-1366 ISSN 0888-613X R&D Projects: GA MŠk 1M0572; GA ČR GEICC/08/E010; GA ČR GA201/09/1891 Grant - others:GA MŠk(CZ) 2C06019 Institutional support: RVO:67985556 Keywords : Bayesian networks * Optimal triangulation * Probabilistic inference * Cliques in a graph Subject RIV: BD - Theory of Information Impact factor: 1.729, year: 2012 http://library.utia.cas.cz/separaty/2012/MTR/vomlel-all roads lead to rome - new search methods for the optimal triangulation problem.pdf
The Medline/full-text research project.
McKinin, E J; Sievert, M; Johnson, E D; Mitchell, J A
1991-05-01
This project was designed to test the relative efficacy of index terms and full-text for the retrieval of documents in those MEDLINE journals for which full-text searching was also available. The full-text files used were MEDIS from Mead Data Central and CCML from BRS Information Technologies. One hundred clinical medical topics were searched in these two files as well as the MEDLINE file to accumulate the necessary data. It was found that full-text identified significantly more relevant articles than did the indexed file, MEDLINE. The full-text searches, however, lacked the precision of searches done in the indexed file. Most relevant items missed in the full-text files, but identified in MEDLINE, were missed because the searcher failed to account for some aspect of natural language, used a logical or positional operator that was too restrictive, or included a concept which was implied, but not expressed in the natural language. Very few of the unique relevant full-text citations would have been retrieved by title or abstract alone. Finally, as of July, 1990 the more current issue of a journal was just as likely to appear in MEDLINE as in one of the full-text files.
Using Text Mining to Uncover Students' Technology-Related Problems in Live Video Streaming
Abdous, M'hammed; He, Wu
2011-01-01
Because of their capacity to sift through large amounts of data, text mining and data mining are enabling higher education institutions to reveal valuable patterns in students' learning behaviours without having to resort to traditional survey methods. In an effort to uncover live video streaming (LVS) students' technology related-problems and to…
Composite Differential Search Algorithm
Directory of Open Access Journals (Sweden)
Bo Liu
2014-01-01
Full Text Available Differential search algorithm (DS is a relatively new evolutionary algorithm inspired by the Brownian-like random-walk movement which is used by an organism to migrate. It has been verified to be more effective than ABC, JDE, JADE, SADE, EPSDE, GSA, PSO2011, and CMA-ES. In this paper, we propose four improved solution search algorithms, namely “DS/rand/1,” “DS/rand/2,” “DS/current to rand/1,” and “DS/current to rand/2” to search the new space and enhance the convergence rate for the global optimization problem. In order to verify the performance of different solution search methods, 23 benchmark functions are employed. Experimental results indicate that the proposed algorithm performs better than, or at least comparable to, the original algorithm when considering the quality of the solution obtained. However, these schemes cannot still achieve the best solution for all functions. In order to further enhance the convergence rate and the diversity of the algorithm, a composite differential search algorithm (CDS is proposed in this paper. This new algorithm combines three new proposed search schemes including “DS/rand/1,” “DS/rand/2,” and “DS/current to rand/1” with three control parameters using a random method to generate the offspring. Experiment results show that CDS has a faster convergence rate and better search ability based on the 23 benchmark functions.
DEFF Research Database (Denmark)
Christensen, Jonas Mark; Røpke, Stefan
that serves all the customers. The second stage usesan Adaptive Large Neighborhood Search (ALNS) algorithm to minimise the travel distance, during the second phase all of the generated routes are considered by solving a set cover problem. The ALNS algorithm uses 4 destroy operators, 2 repair operators...
Construction Example for Algebra System Using Harmony Search Algorithm
Directory of Open Access Journals (Sweden)
FangAn Deng
2015-01-01
Full Text Available The construction example of algebra system is to verify the existence of a complex algebra system, and it is a NP-hard problem. In this paper, to solve this kind of problems, firstly, a mathematical optimization model for construction example of algebra system is established. Secondly, an improved harmony search algorithm based on NGHS algorithm (INGHS is proposed to find as more solutions as possible for the optimization model; in the proposed INGHS algorithm, to achieve the balance between exploration power and exploitation power in the search process, a global best strategy and parameters dynamic adjustment method are present. Finally, nine construction examples of algebra system are used to evaluate the optimization model and performance of INGHS. The experimental results show that the proposed algorithm has strong performance for solving complex construction example problems of algebra system.
Experimental problems of search for quark-gluon plasma in nucleus-nucleus interactions
International Nuclear Information System (INIS)
Okonov, Eh.O.
1987-01-01
Experimental problems for searching for quark-gluon (quagma) plasma in nucleus-nucleus interactions (NbNb,CaCa, ArPb, CnE, ONe) in the energy range E=0.4-1 GeV/A and 3.67 GeV/A and 200 GeV/A energies are discussed. Peculiarities of performing experiments on Dubna synchrophasotron and SPS Bevalac are discussed. The first results prove hadron matter thermalization sufficient for quagma manifestation. It is found that such characteristics of studied interactions as relative λ-hyperon yield, spectral (temperature) characteristics of λ k -hyperons (with higher values of transferred transverse momenta) and associatively produced peons are of greatest interest. The necessity of precise establishment of λ-hyperon group as excessive and differing in its origin from the other particles of the hadron phase is noted. It is shown that experimental approach used in Dubna research proved efficient and requires further development. It includes : selection of rare events (fluctuations) in central interactions of nuclei with high local excitation; search and research of peculiarities in the production of strange particles and in associative pion production; use of streamer spectrometer with a trigger system of rigid selection of central interactions
Lim, Wee Loon; Wibowo, Antoni; Desa, Mohammad Ishak; Haron, Habibollah
2016-01-01
The quadratic assignment problem (QAP) is an NP-hard combinatorial optimization problem with a wide variety of applications. Biogeography-based optimization (BBO), a relatively new optimization technique based on the biogeography concept, uses the idea of migration strategy of species to derive algorithm for solving optimization problems. It has been shown that BBO provides performance on a par with other optimization methods. A classical BBO algorithm employs the mutation operator as its diversification strategy. However, this process will often ruin the quality of solutions in QAP. In this paper, we propose a hybrid technique to overcome the weakness of classical BBO algorithm to solve QAP, by replacing the mutation operator with a tabu search procedure. Our experiments using the benchmark instances from QAPLIB show that the proposed hybrid method is able to find good solutions for them within reasonable computational times. Out of 61 benchmark instances tested, the proposed method is able to obtain the best known solutions for 57 of them.
Lim, Wee Loon; Wibowo, Antoni; Desa, Mohammad Ishak; Haron, Habibollah
2016-01-01
The quadratic assignment problem (QAP) is an NP-hard combinatorial optimization problem with a wide variety of applications. Biogeography-based optimization (BBO), a relatively new optimization technique based on the biogeography concept, uses the idea of migration strategy of species to derive algorithm for solving optimization problems. It has been shown that BBO provides performance on a par with other optimization methods. A classical BBO algorithm employs the mutation operator as its diversification strategy. However, this process will often ruin the quality of solutions in QAP. In this paper, we propose a hybrid technique to overcome the weakness of classical BBO algorithm to solve QAP, by replacing the mutation operator with a tabu search procedure. Our experiments using the benchmark instances from QAPLIB show that the proposed hybrid method is able to find good solutions for them within reasonable computational times. Out of 61 benchmark instances tested, the proposed method is able to obtain the best known solutions for 57 of them. PMID:26819585
DEFF Research Database (Denmark)
Pisinger, David; Røpke, Stefan
2010-01-01
Heuristics based on large neighborhood search have recently shown outstanding results in solving various transportation and scheduling problems. Large neighborhood search methods explore a complex neighborhood by use of heuristics. Using large neighborhoods makes it possible to find better...... candidate solutions in each iteration and hence traverse a more promising search path. Starting from the large neighborhood search method,we give an overview of very large scale neighborhood search methods and discuss recent variants and extensions like variable depth search and adaptive large neighborhood...
Frijters, Paul; Johnston, David W; Lordan, Grace; Shields, Michael A
2013-05-01
There is considerable policy interest in the impact of macroeconomic conditions on health-related behaviours and outcomes. This paper sheds new light on this issue by exploring the relationship between macroeconomic conditions and an indicator of problem drinking derived from state-level data on alcoholism-related Google searches conducted in the US over the period 2004-2011. We find the current recessionary period coincided with an almost 20% increase in alcoholism-related searches. Controlling for state and time-effects, a 5% rise in unemployment is followed in the next 12 months by an approximate 15% increase in searches. The use of Internet searches to inform on health-related behaviours and outcomes is in its infancy; but we suggest that the data provides important real-time information for policy-makers and can help to overcome the under-reporting in surveys of sensitive information. Copyright © 2013 Elsevier Ltd. All rights reserved.
Kushniruk, Andre W; Kan, Min-Yem; McKeown, Kathleen; Klavans, Judith; Jordan, Desmond; LaFlamme, Mark; Patel, Vimia L
2002-01-01
This paper describes the comparative evaluation of an experimental automated text summarization system, Centrifuser and three conventional search engines - Google, Yahoo and About.com. Centrifuser provides information to patients and families relevant to their questions about specific health conditions. It then produces a multidocument summary of articles retrieved by a standard search engine, tailored to the user's question. Subjects, consisting of friends or family of hospitalized patients, were asked to "think aloud" as they interacted with the four systems. The evaluation involved audio- and video recording of subject interactions with the interfaces in situ at a hospital. Results of the evaluation show that subjects found Centrifuser's summarization capability useful and easy to understand. In comparing Centrifuser to the three search engines, subjects' ratings varied; however, specific interface features were deemed useful across interfaces. We conclude with a discussion of the implications for engineering Web-based retrieval systems.
Fuchs, Lynn S.; Gilbert, Jennifer K.; Fuchs, Douglas; Seethaler, Pamela M.; Martin, BrittanyLee N.
2018-01-01
This study was designed to deepen insights on whether word-problem (WP) solving is a form of text comprehension (TC) and on the role of language in WPs. A sample of 325 second graders, representing high, average, and low reading and math performance, was assessed on (a) start-of-year TC, WP skill, language, nonlinguistic reasoning, working memory, and foundational skill (word identification, arithmetic) and (b) year-end WP solving, WP-language processing (understanding WP statements, without calculation demands), and calculations. Multivariate, multilevel path analysis, accounting for classroom and school effects, indicated that TC was a significant and comparably strong predictor of all outcomes. Start-of-year language was a significantly stronger predictor of both year-end WP outcomes than of calculations, whereas start-of-year arithmetic was a significantly stronger predictor of calculations than of either WP measure. Implications are discussed in terms of WP solving as a form of TC and a theoretically coordinated approach, focused on language, for addressing TC and WP-solving instruction. PMID:29643723
Ringed Seal Search for Global Optimization via a Sensitive Search Model.
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Younes Saadi
Full Text Available The efficiency of a metaheuristic algorithm for global optimization is based on its ability to search and find the global optimum. However, a good search often requires to be balanced between exploration and exploitation of the search space. In this paper, a new metaheuristic algorithm called Ringed Seal Search (RSS is introduced. It is inspired by the natural behavior of the seal pup. This algorithm mimics the seal pup movement behavior and its ability to search and choose the best lair to escape predators. The scenario starts once the seal mother gives birth to a new pup in a birthing lair that is constructed for this purpose. The seal pup strategy consists of searching and selecting the best lair by performing a random walk to find a new lair. Affected by the sensitive nature of seals against external noise emitted by predators, the random walk of the seal pup takes two different search states, normal state and urgent state. In the normal state, the pup performs an intensive search between closely adjacent lairs; this movement is modeled via a Brownian walk. In an urgent state, the pup leaves the proximity area and performs an extensive search to find a new lair from sparse targets; this movement is modeled via a Levy walk. The switch between these two states is realized by the random noise emitted by predators. The algorithm keeps switching between normal and urgent states until the global optimum is reached. Tests and validations were performed using fifteen benchmark test functions to compare the performance of RSS with other baseline algorithms. The results show that RSS is more efficient than Genetic Algorithm, Particles Swarm Optimization and Cuckoo Search in terms of convergence rate to the global optimum. The RSS shows an improvement in terms of balance between exploration (extensive and exploitation (intensive of the search space. The RSS can efficiently mimic seal pups behavior to find best lair and provide a new algorithm to be
A Cooperative Harmony Search Algorithm for Function Optimization
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Gang Li
2014-01-01
Full Text Available Harmony search algorithm (HS is a new metaheuristic algorithm which is inspired by a process involving musical improvisation. HS is a stochastic optimization technique that is similar to genetic algorithms (GAs and particle swarm optimizers (PSOs. It has been widely applied in order to solve many complex optimization problems, including continuous and discrete problems, such as structure design, and function optimization. A cooperative harmony search algorithm (CHS is developed in this paper, with cooperative behavior being employed as a significant improvement to the performance of the original algorithm. Standard HS just uses one harmony memory and all the variables of the object function are improvised within the harmony memory, while the proposed algorithm CHS uses multiple harmony memories, so that each harmony memory can optimize different components of the solution vector. The CHS was then applied to function optimization problems. The results of the experiment show that CHS is capable of finding better solutions when compared to HS and a number of other algorithms, especially in high-dimensional problems.
The Scatter Search Based Algorithm to Revenue Management Problem in Broadcasting Companies
Pishdad, Arezoo; Sharifyazdi, Mehdi; Karimpour, Reza
2009-09-01
The problem under question in this paper which is faced by broadcasting companies is how to benefit from a limited advertising space. This problem is due to the stochastic behavior of customers (advertiser) in different fare classes. To address this issue we propose a mathematical constrained nonlinear multi period model which incorporates cancellation and overbooking. The objective function is to maximize the total expected revenue and our numerical method performs it by determining the sales limits for each class of customer to present the revenue management control policy. Scheduling the advertising spots in breaks is another area of concern and we consider it as a constraint in our model. In this paper an algorithm based on Scatter search is developed to acquire a good feasible solution. This method uses simulation over customer arrival and in a continuous finite time horizon [0, T]. Several sensitivity analyses are conducted in computational result for depicting the effectiveness of proposed method. It also provides insight into better results of considering revenue management (control policy) compared to "no sales limit" policy in which sooner demand will served first.
VOICE PROBLEMS IN TRANSLATIONS OF ROMANIAN AND ENGLISH ECONOMIC TEXTS
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Sim Monica Ariana
2011-07-01
Full Text Available The difficulties brought about by the passive constructions have been an issue to debate for many linguists and scientist. Translations become ever more important in an increasingly global marketplace, and they are sometimes taken too lightly, when in fact it is a serious business that should be approached sensibly in order to avoid poor results. Translation is a specialised branch of translation, which requires specific skills and also methodology, theme as well as terminology competences. Without being exhaustive the aim of our paper is to focus on the types of the passive constructions specific to the scientific discourse, the economic one, in particular. It also tackles the translation difficulties that may come along when dealing with scientific papers and rendering texts from Romanian into English. Passive constructions are frequently used both in English and Romanian. However, active forms are more common in literary writing or where the focus is on the people who make things happen. In contrast, passives are mainly specific to texts where the focus is on events and processes, in things that happen. The most common problem in writing economic texts is overusing the passive voice. Specialists recommend or even require the passive voice in scientific, technical writing; motivating that by using the passive voice in scientific writing it achieves an objective tone whereas, sometimes it only obscure the text. The scientific discourse and the economic one in particular, basically mean presenting ideas, descriptions, definitions, classifications, instructions, etc. The speech is brief, the technical person, and the scientist managing to say things which in ordinary language would require a vast amount of talk. Therefore, speakers or writers use the passive constructions in the scientific discourse for the following reasons: a when there is no use of identifying the agent of the action, being unimportant or obvious from the context; b to avoid
LITURGICAL TEXT IN RUSSIAN LITERATURE. PROBLEM STATEMENT
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Avetis Serezhaevich Seropyan
2012-11-01
Full Text Available The article analyses artistic expressions of liturgical language in the literary text and its interaction of the Holy Tradition. Many Russian authors knew the liturgical text well. Studying it reveals the crucial meaning of the Gospel and liturgical texts (as part of the Holy Tradition for Russian literature. Authors saw the essence of every phenomenon in the word for it, and the nature of God in His name. Some ideas and sayings of the authors and their characters find their sources in liturgical texts. The article focuses on liturgical sources of some characters' commemorations and invocations, as well as poetical topics of the symbolists, Dostoevsky's famous dictum on beauty which will save the world (The Idiot, etc. De-cyphering this liturgical code will help us learn and comprehend the hidden endless meaning of a literary text. The specific feature of Russian literature is its pursuit of the spiritual liturgical exploration of the world, an exploration when truth takes shape and thus becomes real in both literary text and history.
Multi-Agent Cooperative Target Search
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Jinwen Hu
2014-05-01
Full Text Available This paper addresses a vision-based cooperative search for multiple mobile ground targets by a group of unmanned aerial vehicles (UAVs with limited sensing and communication capabilities. The airborne camera on each UAV has a limited field of view and its target discriminability varies as a function of altitude. First, by dividing the whole surveillance region into cells, a probability map can be formed for each UAV indicating the probability of target existence within each cell. Then, we propose a distributed probability map updating model which includes the fusion of measurement information, information sharing among neighboring agents, information decay and transmission due to environmental changes such as the target movement. Furthermore, we formulate the target search problem as a multi-agent cooperative coverage control problem by optimizing the collective coverage area and the detection performance. The proposed map updating model and the cooperative control scheme are distributed, i.e., assuming that each agent only communicates with its neighbors within its communication range. Finally, the effectiveness of the proposed algorithms is illustrated by simulation.
Hamadi, Youssef; Saubion, Frédéric
2012-01-01
Autonomous combinatorial search (AS) represents a new field in combinatorial problem solving. Its major standpoint and originality is that it considers that problem solvers must be capable of self-improvement operations. This is the first book dedicated to AS.
Subject search study. Final report
International Nuclear Information System (INIS)
Todeschini, C.
1995-01-01
The study gathered information on how users search the database of the International Nuclear Information System (INIS), using indicators such as Subject categories, Controlled terms, Subject headings, Free-text words, combinations of the above. Users participated from the Australian, French, Russian and Spanish INIS Centres, that have different national languages. Participants, both intermediaries and end users, replied to a questionnaire and executed search queries. The INIS Secretariat at the IAEA also participated. A protocol of all search strategies used in actual searches in the database was kept. The thought process for Russian and Spanish users is predominantly non-English and also the actual initial search formulation is predominantly non-English among Russian and Spanish users while it tends to be more in English among French users. A total of 1002 searches were executed by the five INIS centres including the IAEA. The search protocols indicate the following search behaviour: 1) free text words represent about 40% of search points on an average query; 2) descriptors used as search keys have the widest range as percentage of search points, from a low of 25% to a high of 48%; 3) search keys consisting of free text that coincides with a descriptor account for about 15% of search points; 4) Subject Categories are not used in many searches; 5) free text words are present as search points in about 80% of all searches; 6) controlled terms (descriptors) are used very extensively and appear in about 90% of all searches; 7) Subject Headings were used in only a few percent of searches. From the results of the study one can conclude that there is a greater reluctance on the part of non-native English speakers in initiating their searches by using free text word searches. Also: Subject Categories are little used in searching the database; both free text terms and controlled terms are the predominant types of search keys used, whereby the controlled terms are used more
Fymat, A. L.
1976-01-01
The paper studies the inversion of the radiative transfer equation describing the interaction of electromagnetic radiation with atmospheric aerosols. The interaction can be considered as the propagation in the aerosol medium of two light beams: the direct beam in the line-of-sight attenuated by absorption and scattering, and the diffuse beam arising from scattering into the viewing direction, which propagates more or less in random fashion. The latter beam has single scattering and multiple scattering contributions. In the former case and for single scattering, the problem is reducible to first-kind Fredholm equations, while for multiple scattering it is necessary to invert partial integrodifferential equations. A nonlinear minimization search method, applicable to the solution of both types of problems has been developed, and is applied here to the problem of monitoring aerosol pollution, namely the complex refractive index and size distribution of aerosol particles.
A Typed Text Retrieval Query Language for XML Documents.
Colazzo, Dario; Sartiani, Carlo; Albano, Antonio; Manghi, Paolo; Ghelli, Giorgio; Lini, Luca; Paoli, Michele
2002-01-01
Discussion of XML focuses on a description of Tequyla-TX, a typed text retrieval query language for XML documents that can search on both content and structures. Highlights include motivations; numerous examples; word-based and char-based searches; tag-dependent full-text searches; text normalization; query algebra; data models and term language;…
Deep Web Search Interface Identification: A Semi-Supervised Ensemble Approach
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Hong Wang
2014-12-01
Full Text Available To surface the Deep Web, one crucial task is to predict whether a given web page has a search interface (searchable HyperText Markup Language (HTML form or not. Previous studies have focused on supervised classification with labeled examples. However, labeled data are scarce, hard to get and requires tediousmanual work, while unlabeled HTML forms are abundant and easy to obtain. In this research, we consider the plausibility of using both labeled and unlabeled data to train better models to identify search interfaces more effectively. We present a semi-supervised co-training ensemble learning approach using both neural networks and decision trees to deal with the search interface identification problem. We show that the proposed model outperforms previous methods using only labeled data. We also show that adding unlabeled data improves the effectiveness of the proposed model.
International Nuclear Information System (INIS)
Secui, Dinu Calin
2016-01-01
This paper proposes a new metaheuristic algorithm, called Modified Symbiotic Organisms Search (MSOS) algorithm, to solve the economic dispatch problem considering the valve-point effects, the prohibited operating zones (POZ), the transmission line losses, multi-fuel sources, as well as other operating constraints of the generating units and power system. The MSOS algorithm introduces, in all of its phases, new relations to update the solutions to improve its capacity of identifying stable and of high-quality solutions in a reasonable time. Furthermore, to increase the capacity of exploring the MSOS algorithm in finding the most promising zones, it is endowed with a chaotic component generated by the Logistic map. The performance of the modified algorithm and of the original algorithm Symbiotic Organisms Search (SOS) is tested on five systems of different characteristics, constraints and dimensions (13-unit, 40-unit, 80-unit, 160-unit and 320-unit). The results obtained by applying the proposed algorithm (MSOS) show that this has a better performance than other techniques of optimization recently used in solving the economic dispatch problem with valve-point effects. - Highlights: • A new modified SOS algorithm (MSOS) is proposed to solve the EcD problem. • Valve-point effects, ramp-rate limits, POZ, multi-fuel sources, transmission losses were considered. • The algorithm is tested on five systems having 13, 40, 80, 160 and 320 thermal units. • MSOS algorithm outperforms many other optimization techniques.
Kernel Clustering with a Differential Harmony Search Algorithm for Scheme Classification
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Yu Feng
2017-01-01
Full Text Available This paper presents a kernel fuzzy clustering with a novel differential harmony search algorithm to coordinate with the diversion scheduling scheme classification. First, we employed a self-adaptive solution generation strategy and differential evolution-based population update strategy to improve the classical harmony search. Second, we applied the differential harmony search algorithm to the kernel fuzzy clustering to help the clustering method obtain better solutions. Finally, the combination of the kernel fuzzy clustering and the differential harmony search is applied for water diversion scheduling in East Lake. A comparison of the proposed method with other methods has been carried out. The results show that the kernel clustering with the differential harmony search algorithm has good performance to cooperate with the water diversion scheduling problems.
Soffer, Shira; Kareev, Yaakov
2011-01-01
The effects of problem contents and one's scientific background on the detection of correlations and the assessment of their strength were studied using a task that required active data search, assessment of the strength of a correlation, and monetary valuation of the correlation's predictive utility. Participants (N = 72) who were trained either in the natural sciences or in the social sciences and humanities explored data sets differing in contents and actual strength of correlation. Data search was consistent across all variables: Participants drew relatively small samples whose relative sizes would favor the detection of a correlation, if one existed. In contrast, the assessment of the correlation strength and the valuation of its predictive utility were strongly related not only to its objective strength, but also to the correspondence between problem contents and one's scientific background: When the two matched, correlations were judged to be stronger and more valuable than when they did not.
A New Fuzzy Harmony Search Algorithm Using Fuzzy Logic for Dynamic Parameter Adaptation
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Cinthia Peraza
2016-10-01
Full Text Available In this paper, a new fuzzy harmony search algorithm (FHS for solving optimization problems is presented. FHS is based on a recent method using fuzzy logic for dynamic adaptation of the harmony memory accepting (HMR and pitch adjustment (PArate parameters that improve the convergence rate of traditional harmony search algorithm (HS. The objective of the method is to dynamically adjust the parameters in the range from 0.7 to 1. The impact of using fixed parameters in the harmony search algorithm is discussed and a strategy for efficiently tuning these parameters using fuzzy logic is presented. The FHS algorithm was successfully applied to different benchmarking optimization problems. The results of simulation and comparison studies demonstrate the effectiveness and efficiency of the proposed approach.
Abelev, B; Adam, J; Adamová, D; Aggarwal, M M; Rinella, G Aglieri; Agnello, M; Agostinelli, A; Agrawal, N; Ahammed, Z; Ahmad, N; Ahmed, I; Ahn, S U; Ahn, S A; Aimo, I; Aiola, S; Ajaz, M; Akindinov, A; Alam, S N; Aleksandrov, D; Alessandro, B; Alexandre, D; Alici, A; Alkin, A; Alme, J; Alt, T; Altinpinar, S; Altsybeev, I; Alves Garcia Prado, C; Andrei, C; Andronic, A; Anguelov, V; Anielski, J; Antičić, T; Antinori, F; Antonioli, P; Aphecetche, L; Appelshäuser, H; Arcelli, S; Armesto, N; Arnaldi, R; Aronsson, T; Arsene, I C; Arslandok, M; Augustinus, A; Averbeck, R; Awes, T C; Azmi, M D; Bach, M; Badalà, A; Baek, Y W; Bagnasco, S; Bailhache, R; Bala, R; Baldisseri, A; Baltasar Dos Santos Pedrosa, F; Baral, R C; Barbera, R; Barile, F; Barnaföldi, G G; Barnby, L S; Barret, V; Bartke, J; Basile, M; Bastid, N; Basu, S; Bathen, B; Batigne, G; Batista Camejo, A; Batyunya, B; Batzing, P C; Baumann, C; Bearden, I G; Beck, H; Bedda, C; Behera, N K; Belikov, I; Bellini, F; Bellwied, R; Belmont-Moreno, E; Belmont, R; Belyaev, V; Bencedi, G; Beole, S; Berceanu, I; Bercuci, A; Berdnikov, Y; Berenyi, D; Berger, M E; Bertens, R A; Berzano, D; Betev, L; Bhasin, A; Bhat, I R; Bhati, A K; Bhattacharjee, B; Bhom, J; Bianchi, L; Bianchi, N; Bianchin, C; Bielčík, J; Bielčíková, J; Bilandzic, A; Bjelogrlic, S; Blanco, F; Blau, D; Blume, C; Bock, F; Bogdanov, A; Bøggild, H; Bogolyubsky, M; Böhmer, F V; Boldizsár, L; Bombara, M; Book, J; Borel, H; Borissov, A; Bossú, F; Botje, M; Botta, E; Böttger, S; Braun-Munzinger, P; Bregant, M; Breitner, T; Broker, T A; Browning, T A; Broz, M; Bruna, E; Bruno, G E; Budnikov, D; Buesching, H; Bufalino, S; Buncic, P; Busch, O; Buthelezi, Z; Caffarri, D; Cai, X; Caines, H; Calero Diaz, L; Caliva, A; Calvo Villar, E; Camerini, P; Carena, F; Carena, W; Castillo Castellanos, J; Casula, E A R; Catanescu, V; Cavicchioli, C; Ceballos Sanchez, C; Cepila, J; Cerello, P; Chang, B; Chapeland, S; Charvet, J L; Chattopadhyay, S; Chattopadhyay, S; Chelnokov, V; Cherney, M; Cheshkov, C; Cheynis, B; Chibante Barroso, V; Chinellato, D D; Chochula, P; Chojnacki, M; Choudhury, S; Christakoglou, P; Christensen, C H; Christiansen, P; Chujo, T; Chung, S U; Cicalo, C; Cifarelli, L; Cindolo, F; Cleymans, J; Colamaria, F; Colella, D; Collu, A; Colocci, M; Conesa Balbastre, G; Conesa Del Valle, Z; Connors, M E; Contreras, J G; Cormier, T M; Corrales Morales, Y; Cortese, P; Cortés Maldonado, I; Cosentino, M R; Costa, F; Crochet, P; Cruz Albino, R; Cuautle, E; Cunqueiro, L; Dainese, A; Dang, R; Danu, A; Das, D; Das, I; Das, K; Das, S; Dash, A; Dash, S; De, S; Delagrange, H; Deloff, A; Dénes, E; D'Erasmo, G; De Caro, A; de Cataldo, G; de Cuveland, J; De Falco, A; De Gruttola, D; De Marco, N; De Pasquale, S; de Rooij, R; Diaz Corchero, M A; Dietel, T; Dillenseger, P; Divià, R; Di Bari, D; Di Liberto, S; Di Mauro, A; Di Nezza, P; Djuvsland, Ø; Dobrin, A; Dobrowolski, T; Domenicis Gimenez, D; Dönigus, B; Dordic, O; Dørheim, S; Dubey, A K; Dubla, A; Ducroux, L; Dupieux, P; Dutta Majumdar, A K; Hilden, T E; Ehlers, R J; Elia, D; Engel, H; Erazmus, B; Erdal, H A; Eschweiler, D; Espagnon, B; Esposito, M; Estienne, M; Esumi, S; Evans, D; Evdokimov, S; Fabris, D; Faivre, J; Falchieri, D; Fantoni, A; Fasel, M; Fehlker, D; Feldkamp, L; Felea, D; Feliciello, A; Feofilov, G; Ferencei, J; Fernández Téllez, A; Ferreiro, E G; Ferretti, A; Festanti, A; Figiel, J; Figueredo, M A S; Filchagin, S; Finogeev, D; Fionda, F M; Fiore, E M; Floratos, E; Floris, M; Foertsch, S; Foka, P; Fokin, S; Fragiacomo, E; Francescon, A; Frankenfeld, U; Fuchs, U; Furget, C; Furs, A; Fusco Girard, M; Gaardhøje, J J; Gagliardi, M; Gago, A M; Gallio, M; Gangadharan, D R; Ganoti, P; Gao, C; Garabatos, C; Garcia-Solis, E; Gargiulo, C; Garishvili, I; Gerhard, J; Germain, M; Gheata, A; Gheata, M; Ghidini, B; Ghosh, P; Ghosh, S K; Gianotti, P; Giubellino, P; Gladysz-Dziadus, E; Glässel, P; Gomez Ramirez, A; González-Zamora, P; Gorbunov, S; Görlich, L; Gotovac, S; Graczykowski, L K; Grelli, A; Grigoras, A; Grigoras, C; Grigoriev, V; Grigoryan, A; Grigoryan, S; Grinyov, B; Grion, N; Grosse-Oetringhaus, J F; Grossiord, J-Y; Grosso, R; Guber, F; Guernane, R; Guerzoni, B; Guilbaud, M; Gulbrandsen, K; Gulkanyan, H; Gumbo, M; Gunji, T; Gupta, A; Gupta, R; Khan, K H; Haake, R; Haaland, Ø; Hadjidakis, C; Haiduc, M; Hamagaki, H; Hamar, G; Hanratty, L D; Hansen, A; Harris, J W; Hartmann, H; Harton, A; Hatzifotiadou, D; Hayashi, S; Heckel, S T; Heide, M; Helstrup, H; Herghelegiu, A; Herrera Corral, G; Hess, B A; Hetland, K F; Hippolyte, B; Hladky, J; Hristov, P; Huang, M; Humanic, T J; Hussain, N; Hussain, T; Hutter, D; Hwang, D S; Ilkaev, R; Ilkiv, I; Inaba, M; Innocenti, G M; Ionita, C; Ippolitov, M; Irfan, M; Ivanov, M; Ivanov, V; Jachołkowski, A; Jacobs, P M; Jahnke, C; Jang, H J; Janik, M A; Jayarathna, P H S Y; Jena, C; Jena, S; Jimenez Bustamante, R T; Jones, P G; Jung, H; Jusko, A; Kadyshevskiy, V; Kalinak, P; Kalweit, A; Kamin, J; Kang, J H; Kaplin, V; Kar, S; Karasu Uysal, A; Karavichev, O; Karavicheva, T; Karpechev, E; Kebschull, U; Keidel, R; Keijdener, D L D; Svn, M Keil; Khan, M M; Khan, P; Khan, S A; Khanzadeev, A; Kharlov, Y; Kileng, B; Kim, B; Kim, D W; Kim, D J; Kim, J S; Kim, M; Kim, M; Kim, S; Kim, T; Kirsch, S; Kisel, I; Kiselev, S; Kisiel, A; Kiss, G; Klay, J L; Klein, J; Klein-Bösing, C; Kluge, A; Knichel, M L; Knospe, A G; Kobdaj, C; Kofarago, M; Köhler, M K; Kollegger, T; Kolojvari, A; Kondratiev, V; Kondratyeva, N; Konevskikh, A; Kovalenko, V; Kowalski, M; Kox, S; Koyithatta Meethaleveedu, G; Kral, J; Králik, I; Kravčáková, A; Krelina, M; Kretz, M; Krivda, M; Krizek, F; Kryshen, E; Krzewicki, M; Kučera, V; Kucheriaev, Y; Kugathasan, T; Kuhn, C; Kuijer, P G; Kulakov, I; Kumar, J; Kurashvili, P; Kurepin, A; Kurepin, A B; Kuryakin, A; Kushpil, S; Kweon, M J; Kwon, Y; Ladron de Guevara, P; Lagana Fernandes, C; Lakomov, I; Langoy, R; Lara, C; Lardeux, A; Lattuca, A; La Pointe, S L; La Rocca, P; Lea, R; Leardini, L; Lee, G R; Legrand, I; Lehnert, J; Lemmon, R C; Lenti, V; Leogrande, E; Leoncino, M; León Monzón, I; Lévai, P; Li, S; Lien, J; Lietava, R; Lindal, S; Lindenstruth, V; Lippmann, C; Lisa, M A; Ljunggren, H M; Lodato, D F; Loenne, P I; Loggins, V R; Loginov, V; Lohner, D; Loizides, C; Lopez, X; López Torres, E; Lu, X-G; Luettig, P; Lunardon, M; Luparello, G; Ma, R; Maevskaya, A; Mager, M; Mahapatra, D P; Mahmood, S M; Maire, A; Majka, R D; Malaev, M; Maldonado Cervantes, I; Malinina, L; Mal'Kevich, D; Malzacher, P; Mamonov, A; Manceau, L; Manko, V; Manso, F; Manzari, V; Marchisone, M; Mareš, J; Margagliotti, G V; Margotti, A; Marín, A; Markert, C; Marquard, M; Martashvili, I; Martin, N A; Martinengo, P; Martínez, M I; Martínez García, G; Martin Blanco, J; Martynov, Y; Mas, A; Masciocchi, S; Masera, M; Masoni, A; Massacrier, L; Mastroserio, A; Matyja, A; Mayer, C; Mazer, J; Mazzoni, M A; Meddi, F; Menchaca-Rocha, A; Meninno, E; Mercado Pérez, J; Meres, M; Miake, Y; Mikhaylov, K; Milano, L; Milosevic, J; Mischke, A; Mishra, A N; Miśkowiec, D; Mitra, J; Mitu, C M; Mlynarz, J; Mohammadi, N; Mohanty, B; Molnar, L; Montaño Zetina, L; Montes, E; Morando, M; Moreira De Godoy, D A; Moretto, S; Morreale, A; Morsch, A; Muccifora, V; Mudnic, E; Mühlheim, D; Muhuri, S; Mukherjee, M; Müller, H; Munhoz, M G; Murray, S; Musa, L; Musinsky, J; Nandi, B K; Nania, R; Nappi, E; Nattrass, C; Nayak, K; Nayak, T K; Nazarenko, S; Nedosekin, A; Nicassio, M; Niculescu, M; Niedziela, J; Nielsen, B S; Nikolaev, S; Nikulin, S; Nikulin, V; Nilsen, B S; Noferini, F; Nomokonov, P; Nooren, G; Norman, J; Nyanin, A; Nystrand, J; Oeschler, H; Oh, S; Oh, S K; Okatan, A; Okubo, T; Olah, L; Oleniacz, J; Oliveira Da Silva, A C; Onderwaater, J; Oppedisano, C; Ortiz Velasquez, A; Oskarsson, A; Otwinowski, J; Oyama, K; Ozdemir, M; Sahoo, P; Pachmayer, Y; Pachr, M; Pagano, P; Paić, G; Pajares, C; Pal, S K; Palmeri, A; Pant, D; Papikyan, V; Pappalardo, G S; Pareek, P; Park, W J; Parmar, S; Passfeld, A; Patalakha, D I; Paticchio, V; Paul, B; Pawlak, T; Peitzmann, T; Pereira Da Costa, H; Pereira De Oliveira Filho, E; Peresunko, D; Pérez Lara, C E; Pesci, A; Peskov, V; Pestov, Y; Petráček, V; Petran, M; Petris, M; Petrovici, M; Petta, C; Piano, S; Pikna, M; Pillot, P; Pinazza, O; Pinsky, L; Piyarathna, D B; Płoskoń, M; Planinic, M; Pluta, J; Pochybova, S; Podesta-Lerma, P L M; Poghosyan, M G; Pohjoisaho, E H O; Polichtchouk, B; Poljak, N; Pop, A; Porteboeuf-Houssais, S; Porter, J; Potukuchi, B; Prasad, S K; Preghenella, R; Prino, F; Pruneau, C A; Pshenichnov, I; Puccio, M; Puddu, G; Pujahari, P; Punin, V; Putschke, J; Qvigstad, H; Rachevski, A; Raha, S; Rajput, S; Rak, J; Rakotozafindrabe, A; Ramello, L; Raniwala, R; Raniwala, S; Räsänen, S S; Rascanu, B T; Rathee, D; Rauf, A W; Razazi, V; Read, K F; Real, J S; Redlich, K; Reed, R J; Rehman, A; Reichelt, P; Reicher, M; Reidt, F; Renfordt, R; Reolon, A R; Reshetin, A; Rettig, F; Revol, J-P; Reygers, K; Riabov, V; Ricci, R A; Richert, T; Richter, M; Riedler, P; Riegler, W; Riggi, F; Rivetti, A; Rocco, E; Rodríguez Cahuantzi, M; Rodriguez Manso, A; Røed, K; 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Zhao, C; Zhigareva, N; Zhou, D; Zhou, F; Zhou, Y; Zhuo, Zhou; Zhu, H; Zhu, J; Zhu, X; Zichichi, A; Zimmermann, A; Zimmermann, M B; Zinovjev, G; Zoccarato, Y; Zyzak, M
The production of the strange and double-strange baryon resonances ([Formula: see text], [Formula: see text]) has been measured at mid-rapidity ([Formula: see text][Formula: see text]) in proton-proton collisions at [Formula: see text] [Formula: see text] 7 TeV with the ALICE detector at the LHC. Transverse momentum spectra for inelastic collisions are compared to QCD-inspired models, which in general underpredict the data. A search for the [Formula: see text] pentaquark, decaying in the [Formula: see text] channel, has been carried out but no evidence is seen.
Mohamed, Najihah; Lutfi Amri Ramli, Ahmad; Majid, Ahmad Abd; Piah, Abd Rahni Mt
2017-09-01
A metaheuristic algorithm, called Harmony Search is quite highly applied in optimizing parameters in many areas. HS is a derivative-free real parameter optimization algorithm, and draws an inspiration from the musical improvisation process of searching for a perfect state of harmony. Propose in this paper Modified Harmony Search for solving optimization problems, which employs a concept from genetic algorithm method and particle swarm optimization for generating new solution vectors that enhances the performance of HS algorithm. The performances of MHS and HS are investigated on ten benchmark optimization problems in order to make a comparison to reflect the efficiency of the MHS in terms of final accuracy, convergence speed and robustness.
Complete local search with memory
Ghosh, D.; Sierksma, G.
2000-01-01
Neighborhood search heuristics like local search and its variants are some of the most popular approaches to solve discrete optimization problems of moderate to large size. Apart from tabu search, most of these heuristics are memoryless. In this paper we introduce a new neighborhood search heuristic
A Linear Time Complexity of Breadth-First Search Using P System with Membrane Division
Directory of Open Access Journals (Sweden)
Einallah Salehi
2013-01-01
Full Text Available One of the known methods for solving the problems with exponential time complexity such as NP-complete problems is using the brute force algorithms. Recently, a new parallel computational framework called Membrane Computing is introduced which can be applied in brute force algorithms. The usual way to find a solution for the problems with exponential time complexity with Membrane Computing techniques is by P System with active membrane using division rule. It makes an exponential workspace and solves the problems with exponential complexity in a polynomial (even linear time. On the other hand, searching is currently one of the most used methods for finding solution for problems in real life, that the blind search algorithms are accurate, but their time complexity is exponential such as breadth-first search (BFS algorithm. In this paper, we proposed a new approach for implementation of BFS by using P system with division rule technique for first time. The theorem shows time complexity of BSF in this framework on randomly binary trees reduced from O(2d to O(d.
Double evolutsional artificial bee colony algorithm for multiple traveling salesman problem
Directory of Open Access Journals (Sweden)
Xue Ming Hao
2016-01-01
Full Text Available The double evolutional artificial bee colony algorithm (DEABC is proposed for solving the single depot multiple traveling salesman problem (MTSP. The proposed DEABC algorithm, which takes advantage of the strength of the upgraded operators, is characterized by its guidance in exploitation search and diversity in exploration search. The double evolutional process for exploitation search is composed of two phases of half stochastic optimal search, and the diversity generating operator for exploration search is used for solutions which cannot be improved after limited times. The computational results demonstrated the superiority of our algorithm over previous state-of-the-art methods.
Usability Testing of a Large, Multidisciplinary Library Database: Basic Search and Visual Search
Directory of Open Access Journals (Sweden)
Jody Condit Fagan
2006-09-01
Full Text Available Visual search interfaces have been shown by researchers to assist users with information search and retrieval. Recently, several major library vendors have added visual search interfaces or functions to their products. For public service librarians, perhaps the most critical area of interest is the extent to which visual search interfaces and text-based search interfaces support research. This study presents the results of eight full-scale usability tests of both the EBSCOhost Basic Search and Visual Search in the context of a large liberal arts university.
Current Writing: Text and Reception in Southern Africa: Advanced ...
African Journals Online (AJOL)
Current Writing: Text and Reception in Southern Africa: Advanced Search. Journal Home > Current Writing: Text and Reception in Southern Africa: Advanced Search. Log in or Register to get access to full text downloads.
An Adaptive Evolutionary Algorithm for Traveling Salesman Problem with Precedence Constraints
Directory of Open Access Journals (Sweden)
Jinmo Sung
2014-01-01
Full Text Available Traveling sales man problem with precedence constraints is one of the most notorious problems in terms of the efficiency of its solution approach, even though it has very wide range of industrial applications. We propose a new evolutionary algorithm to efficiently obtain good solutions by improving the search process. Our genetic operators guarantee the feasibility of solutions over the generations of population, which significantly improves the computational efficiency even when it is combined with our flexible adaptive searching strategy. The efficiency of the algorithm is investigated by computational experiments.
LOTUS: Adaptive text search for big linked data
Ilievski, F.; Beek, Wouter; van Erp, Marieke; Rietveld, Laurens; Schlobach, Stefan
2016-01-01
Finding relevant resources on the Semantic Web today is a dirty job: no centralized query service exists and the support for natural language access is limited. We present LOTUS: Linked Open Text Un- leaShed, a text-based entry point to a massive subset of today’s Linked Open Data Cloud. Recognizing
[Systematic literature search in PubMed : A short introduction].
Blümle, A; Lagrèze, W A; Motschall, E
2018-03-01
In order to identify current (and relevant) evidence for a specific clinical question within the unmanageable amount of information available, solid skills in performing a systematic literature search are essential. An efficient approach is to search a biomedical database containing relevant literature citations of study reports. The best known database is MEDLINE, which is searchable for free via the PubMed interface. In this article, we explain step by step how to perform a systematic literature search via PubMed by means of an example research question in the field of ophthalmology. First, we demonstrate how to translate the clinical problem into a well-framed and searchable research question, how to identify relevant search terms and how to conduct a text word search and a search with keywords in medical subject headings (MeSH) terms. We then show how to limit the number of search results if the search yields too many irrelevant hits and how to increase the number in the case of too few citations. Finally, we summarize all essential principles that guide a literature search via PubMed.
Alimorad, Zahra
2015-01-01
This study aimed to discover semantic and syntactic problems Persian native speakers might have while reading English and Persian texts and different strategies they use to overcome those problems. To this end, a convenient sample of 40 intermediate students studying English Literature at Shiraz University was selected. Twenty of them were asked…
Practical fulltext search in medical records
Directory of Open Access Journals (Sweden)
Vít Volšička
2015-09-01
Full Text Available Performing a search through previously existing documents, including medical reports, is an integral part of acquiring new information and educational processes. Unfortunately, finding relevant information is not always easy, since many documents are saved in free text formats, thereby making it difficult to search through them. A full-text search is a viable solution for searching through documents. The full-text search makes it possible to efficiently search through large numbers of documents and to find those that contain specific search phrases in a short time. All leading database systems currently offer full-text search, but some do not support the complex morphology of the Czech language. Apache Solr provides full support options and some full-text libraries. This programme provides the good support of the Czech language in the basic installation, and a wide range of settings and options for its deployment over any platform. The library had been satisfactorily tested using real data from the hospitals. Solr provided useful, fast, and accurate searches. However, there is still a need to make adjustments in order to receive effective search results, particularly by correcting typographical errors made not only in the text, but also when entering words in the search box and creating a list of frequently used abbreviations and synonyms for more accurate results.
An adaptive bin framework search method for a beta-sheet protein homopolymer model
Directory of Open Access Journals (Sweden)
Hoos Holger H
2007-04-01
Full Text Available Abstract Background The problem of protein structure prediction consists of predicting the functional or native structure of a protein given its linear sequence of amino acids. This problem has played a prominent role in the fields of biomolecular physics and algorithm design for over 50 years. Additionally, its importance increases continually as a result of an exponential growth over time in the number of known protein sequences in contrast to a linear increase in the number of determined structures. Our work focuses on the problem of searching an exponentially large space of possible conformations as efficiently as possible, with the goal of finding a global optimum with respect to a given energy function. This problem plays an important role in the analysis of systems with complex search landscapes, and particularly in the context of ab initio protein structure prediction. Results In this work, we introduce a novel approach for solving this conformation search problem based on the use of a bin framework for adaptively storing and retrieving promising locally optimal solutions. Our approach provides a rich and general framework within which a broad range of adaptive or reactive search strategies can be realized. Here, we introduce adaptive mechanisms for choosing which conformations should be stored, based on the set of conformations already stored in memory, and for biasing choices when retrieving conformations from memory in order to overcome search stagnation. Conclusion We show that our bin framework combined with a widely used optimization method, Monte Carlo search, achieves significantly better performance than state-of-the-art generalized ensemble methods for a well-known protein-like homopolymer model on the face-centered cubic lattice.
Fast Optimal Replica Placement with Exhaustive Search Using Dynamically Reconfigurable Processor
Directory of Open Access Journals (Sweden)
Hidetoshi Takeshita
2011-01-01
Full Text Available This paper proposes a new replica placement algorithm that expands the exhaustive search limit with reasonable calculation time. It combines a new type of parallel data-flow processor with an architecture tuned for fast calculation. The replica placement problem is to find a replica-server set satisfying service constraints in a content delivery network (CDN. It is derived from the set cover problem which is known to be NP-hard. It is impractical to use exhaustive search to obtain optimal replica placement in large-scale networks, because calculation time increases with the number of combinations. To reduce calculation time, heuristic algorithms have been proposed, but it is known that no heuristic algorithm is assured of finding the optimal solution. The proposed algorithm suits parallel processing and pipeline execution and is implemented on DAPDNA-2, a dynamically reconfigurable processor. Experiments show that the proposed algorithm expands the exhaustive search limit by the factor of 18.8 compared to the conventional algorithm search limit running on a Neumann-type processor.
Approximate search for Big Data with applications in information security – A survey
Directory of Open Access Journals (Sweden)
Slobodan Petrović
2015-04-01
Full Text Available This paper is a survey of approximate search techniques in very large data sets (so-called Big Data. After a short introduction, some techniques for speeding up approximate search in such data sets based on exploitation of inherent bit-parallelism in computers are described. It then reviews the applications in search related to information security problems (digital forensics, malware detection, intrusion detection are reviewed. Finally, the need for constraints in approximate search regarding the number of so-called elementary edit operations and the run lengths of particular elementary edit operations is explained and the status of on-going research on efficient implementation of approximate search algorithms with various constraints is given.
Tales from the Field: Search Strategies Applied in Web Searching
Directory of Open Access Journals (Sweden)
Soohyung Joo
2010-08-01
Full Text Available In their web search processes users apply multiple types of search strategies, which consist of different search tactics. This paper identifies eight types of information search strategies with associated cases based on sequences of search tactics during the information search process. Thirty-one participants representing the general public were recruited for this study. Search logs and verbal protocols offered rich data for the identification of different types of search strategies. Based on the findings, the authors further discuss how to enhance web-based information retrieval (IR systems to support each type of search strategy.
Heuristics for the Robust Coloring Problem
Directory of Open Access Journals (Sweden)
Miguel Ángel Gutiérrez Andrade
2011-03-01
Full Text Available Let $G$ and $\\bar{G}$ be complementary graphs. Given a penalty function defined on the edges of $G$, we will say that the rigidity of a $k$-coloring of $G$ is the sum of the penalties of the edges of G joining vertices of the same color. Based on the previous definition, the Robust Coloring Problem (RCP is stated as the search of the minimum rigidity $k$-coloring. In this work a comparison of heuristics based on simulated annealing, GRASP and scatter search is presented. These are the best results for the RCP that have been obtained.
Search of the Deep and Dark Web via DARPA Memex
Mattmann, C. A.
2015-12-01
Search has progressed through several stages due to the increasing size of the Web. Search engines first focused on text and its rate of occurrence; then focused on the notion of link analysis and citation then on interactivity and guided search; and now on the use of social media - who we interact with, what we comment on, and who we follow (and who follows us). The next stage, referred to as "deep search," requires solutions that can bring together text, images, video, importance, interactivity, and social media to solve this challenging problem. The Apache Nutch project provides an open framework for large-scale, targeted, vertical search with capabilities to support all past and potential future search engine foci. Nutch is a flexible infrastructure allowing open access to ranking; URL selection and filtering approaches, to the link graph generated from search, and Nutch has spawned entire sub communities including Apache Hadoop and Apache Tika. It addresses many current needs with the capability to support new technologies such as image and video. On the DARPA Memex project, we are creating create specific extensions to Nutch that will directly improve its overall technological superiority for search and that will directly allow us to address complex search problems including human trafficking. We are integrating state-of-the-art algorithms developed by Kitware for IARPA Aladdin combined with work by Harvard to provide image and video understanding support allowing automatic detection of people and things and massive deployment via Nutch. We are expanding Apache Tika for scene understanding, object/person detection and classification in images/video. We are delivering an interactive and visual interface for initiating Nutch crawls. The interface uses Python technologies to expose Nutch data and to provide a domain specific language for crawls. With the Bokeh visualization library the interface we are delivering simple interactive crawl visualization and
Young adult international adoptees' search for birth parents.
Tieman, Wendy; van der Ende, Jan; Verhulst, Frank C
2008-10-01
This study examines international adoptees and factors associated with searching for birth parents. A total of 1,417 international adoptees in The Netherlands, aged 24 to 30 years, were divided into 4 groups: uninterested nonsearchers, interested nonsearchers, searchers, and reunited searchers. In total, 32% of adoptees had searched. Although the majority of searchers were well-adjusted, they had more problems--mainly internalizing problems--than uninterested nonsearchers. These problems, however, were not caused by the search itself. It is concluded that searching is the product of natural curiosity influenced by external factors such as the divorce of adoptive parents and the options for searching. Copyright 2008 APA, all rights reserved.
A HYBRID HEURISTIC ALGORITHM FOR THE CLUSTERED TRAVELING SALESMAN PROBLEM
Directory of Open Access Journals (Sweden)
Mário Mestria
2016-04-01
Full Text Available ABSTRACT This paper proposes a hybrid heuristic algorithm, based on the metaheuristics Greedy Randomized Adaptive Search Procedure, Iterated Local Search and Variable Neighborhood Descent, to solve the Clustered Traveling Salesman Problem (CTSP. Hybrid Heuristic algorithm uses several variable neighborhood structures combining the intensification (using local search operators and diversification (constructive heuristic and perturbation routine. In the CTSP, the vertices are partitioned into clusters and all vertices of each cluster have to be visited contiguously. The CTSP is -hard since it includes the well-known Traveling Salesman Problem (TSP as a special case. Our hybrid heuristic is compared with three heuristics from the literature and an exact method. Computational experiments are reported for different classes of instances. Experimental results show that the proposed hybrid heuristic obtains competitive results within reasonable computational time.
Directory of Open Access Journals (Sweden)
Rafael de Carvalho Miranda
2014-01-01
Full Text Available The development of discrete-event simulation software was one of the most successful interfaces in operational research with computation. As a result, research has been focused on the development of new methods and algorithms with the purpose of increasing simulation optimization efficiency and reliability. This study aims to define optimum variation intervals for each decision variable through a proposed approach which combines the data envelopment analysis with the Fuzzy logic (Fuzzy-DEA-BCC, seeking to improve the decision-making units’ distinction in the face of uncertainty. In this study, Taguchi’s orthogonal arrays were used to generate the necessary quantity of DMUs, and the output variables were generated by the simulation. Two study objects were utilized as examples of mono- and multiobjective problems. Results confirmed the reliability and applicability of the proposed method, as it enabled a significant reduction in search space and computational demand when compared to conventional simulation optimization techniques.
When Gravity Fails: Local Search Topology
Frank, Jeremy; Cheeseman, Peter; Stutz, John; Lau, Sonie (Technical Monitor)
1997-01-01
Local search algorithms for combinatorial search problems frequently encounter a sequence of states in which it is impossible to improve the value of the objective function; moves through these regions, called {\\em plateau moves), dominate the time spent in local search. We analyze and characterize {\\em plateaus) for three different classes of randomly generated Boolean Satisfiability problems. We identify several interesting features of plateaus that impact the performance of local search algorithms. We show that local minima tend to be small but occasionally may be very large. We also show that local minima can be escaped without unsatisfying a large number of clauses, but that systematically searching for an escape route may be computationally expensive if the local minimum is large. We show that plateaus with exits, called benches, tend to be much larger than minima, and that some benches have very few exit states which local search can use to escape. We show that the solutions (i.e. global minima) of randomly generated problem instances form clusters, which behave similarly to local minima. We revisit several enhancements of local search algorithms and explain their performance in light of our results. Finally we discuss strategies for creating the next generation of local search algorithms.
Search along persistent random walks
International Nuclear Information System (INIS)
Friedrich, Benjamin M
2008-01-01
Optimal search strategies and their implementations in biological systems are a subject of active research. Here we study a search problem which is motivated by the hunt of sperm cells for the egg. We ask for the probability for an active swimmer to find a target under the condition that the swimmer starts at a certain distance from the target. We find that success probability is maximal for a certain level of fluctuations characterized by the persistence length of the swimming path of the swimmer. We derive a scaling law for the optimal persistence length as a function of the initial target distance and search time by mapping the search on a polymer physics problem
Local search heuristics for the probabilistic dial-a-ride problem
DEFF Research Database (Denmark)
Ho, Sin C.; Haugland, Dag
2011-01-01
evaluation procedure in a pure local search heuristic and in a tabu search heuristic. The quality of the solutions obtained by the two heuristics have been compared experimentally. Computational results confirm that our neighborhood evaluation technique is much faster than the straightforward one...
Collaborative Search Strategies for Green Innovation
DEFF Research Database (Denmark)
Ørding Olsen, Anders; Sofka, Wolfgang; Grimpe, Christoph
Recent innovation and strategy research emphasizes the importance of firm’s search for external knowledge to improve innovation performance. We focus on such search strategies within the domain of sustainable innovation in which problems are inherently complex and the relevant knowledge is widely...... dispersed. Hence, firms need to collaborate. We shed new light on collaborative search strategies led by firms in general and for solving environmental problems in particular. Both topics are largely absent in the extant open innovation literature. Using data from the European Seventh Framework Program...... for Research and Technological Development (FP7), our results indicate that the problem-solving potential of a search strategy increases with the diversity of existing knowledge of the partners in a consortium and with the experience of the partners involved. Moreover, we identify a substantial negative effect...
AUTHOR|(INSPIRE)INSPIRE-00390052; Schöning, André;; Schultz-Coulon, Hans-Christian.
Cosmological and astrophysical observations indicate the existence of Dark Matter. Many beyond Standard Model theories predict associated production of Dark Matter particles with a Higgs boson at energies that can be probed at collider experiments. The signature of the presented analysis consists of a $b\\bar{b}$ pair from a Higgs boson decay recoiling against missing transverse momentum from Dark Matter particles, $h(\\rightarrow b\\bar{b})+E_{T}^{miss}$. The presented $h(\\rightarrow b\\bar{b})+E_{T}^{miss}$ search is performed using proton-proton collisions at a centre-of-mass energy of $13~\\text{TeV}$ with an integrated luminosity of $36.1~\\text{fb}^{-1}$ recorded with the ATLAS detector at the Large Hadron Collider. Several new refined event selections were developed, which increase considerably the experimental sensitivity of the search to beyond Standard Model theories resulting in a $h(\\rightarrow b\\bar{b})+E_{T}^{miss}$ signature. Discovery significance along with its gains from the new refined event sel...
Optimal Search Strategy of Robotic Assembly Based on Neural Vibration Learning
Directory of Open Access Journals (Sweden)
Lejla Banjanovic-Mehmedovic
2011-01-01
Full Text Available This paper presents implementation of optimal search strategy (OSS in verification of assembly process based on neural vibration learning. The application problem is the complex robot assembly of miniature parts in the example of mating the gears of one multistage planetary speed reducer. Assembly of tube over the planetary gears was noticed as the most difficult problem of overall assembly. The favourable influence of vibration and rotation movement on compensation of tolerance was also observed. With the proposed neural-network-based learning algorithm, it is possible to find extended scope of vibration state parameter. Using optimal search strategy based on minimal distance path between vibration parameter stage sets (amplitude and frequencies of robots gripe vibration and recovery parameter algorithm, we can improve the robot assembly behaviour, that is, allow the fastest possible way of mating. We have verified by using simulation programs that search strategy is suitable for the situation of unexpected events due to uncertainties.
Directory of Open Access Journals (Sweden)
Mei-Shiang Chang
2013-01-01
Full Text Available The facility layout problem is a typical combinational optimization problem. In this research, a slicing tree representation and a quadratically constrained program model are combined with harmony search to develop a heuristic method for solving the unequal-area block layout problem. Because of characteristics of slicing tree structure, we propose a regional structure of harmony memory to memorize facility layout solutions and two kinds of harmony improvisation to enhance global search ability of the proposed heuristic method. The proposed harmony search based heuristic is tested on 10 well-known unequal-area facility layout problems from the literature. The results are compared with the previously best-known solutions obtained by genetic algorithm, tabu search, and ant system as well as exact methods. For problems O7, O9, vC10Ra, M11*, and Nug12, new best solutions are found. For other problems, the proposed approach can find solutions that are very similar to previous best-known solutions.
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Socher, F; Soffer, A; Soh, D A; Sokhrannyi, G; Solans Sanchez, C A; Solar, M; Soldatov, E Yu; Soldevila, U; Solodkov, A A; Soloshenko, A; Solovyanov, O V; Solovyev, V; Sommer, P; Son, H; Sopczak, A; Sosa, D; Sotiropoulou, C L; Soualah, R; Soukharev, A M; South, D; Sowden, B C; Spagnolo, S; Spalla, M; Spangenberg, M; Spanò, F; Sperlich, D; Spettel, F; Spieker, T M; Spighi, R; Spigo, G; Spiller, L A; Spousta, M; St Denis, R D; Stabile, A; Stamen, R; Stamm, S; Stanecka, E; Stanek, R W; Stanescu, C; Stanitzki, M M; Stapf, B S; Stapnes, S; Starchenko, E A; Stark, G H; Stark, J; Stark, S H; Staroba, P; Starovoitov, P; Stärz, S; Staszewski, R; Steinberg, P; Stelzer, B; Stelzer, H J; Stelzer-Chilton, O; Stenzel, H; Stewart, G A; Stockton, M C; Stoebe, M; Stoicea, G; Stolte, P; Stonjek, S; Stradling, A R; Straessner, A; Stramaglia, M E; Strandberg, J; Strandberg, S; Strauss, M; Strizenec, P; Ströhmer, R; Strom, D M; Stroynowski, R; Strubig, A; Stucci, S A; Stugu, B; Styles, N A; Su, D; Su, J; Suchek, S; Sugaya, Y; Suk, M; Sulin, V V; Sultan, D M S; Sultansoy, S; Sumida, T; Sun, S; Sun, X; Suruliz, K; Suster, C J E; Sutton, M R; Suzuki, S; Svatos, M; Swiatlowski, M; Swift, S P; Sykora, I; Sykora, T; Ta, D; Tackmann, K; Taenzer, J; Taffard, A; Tafirout, R; Taiblum, N; Takai, H; Takashima, R; Takasugi, E H; Takeshita, T; Takubo, Y; Talby, M; Talyshev, A A; Tanaka, J; Tanaka, M; Tanaka, R; Tanaka, S; Tanioka, R; Tannenwald, B B; Tapia Araya, S; Tapprogge, S; Tarem, S; Tartarelli, G F; Tas, P; Tasevsky, M; Tashiro, T; Tassi, E; Tavares Delgado, A; Tayalati, Y; Taylor, A C; Taylor, G N; Taylor, P T E; Taylor, W; Teixeira-Dias, P; Temple, D; Ten Kate, H; Teng, P K; Teoh, J J; Tepel, F; Terada, S; Terashi, K; Terron, J; Terzo, S; Testa, M; Teuscher, R J; Theveneaux-Pelzer, T; Thomas, J P; Thomas-Wilsker, J; Thompson, P D; Thompson, A S; Thomsen, L A; Thomson, E; Tibbetts, M J; Ticse Torres, R E; Tikhomirov, V O; Tikhonov, Yu A; Timoshenko, S; Tipton, P; Tisserant, S; Todome, K; Todorova-Nova, S; Tojo, J; Tokár, S; Tokushuku, K; Tolley, E; Tomlinson, L; Tomoto, M; Tompkins, L; Toms, K; Tong, B; Tornambe, P; Torrence, E; Torres, H; Torró Pastor, E; Toth, J; Touchard, F; Tovey, D R; Treado, C J; Trefzger, T; Tresoldi, F; Tricoli, A; Trigger, I M; Trincaz-Duvoid, S; Tripiana, M F; Trischuk, W; Trocmé, B; Trofymov, A; Troncon, C; Trottier-McDonald, M; Trovatelli, M; Truong, L; Trzebinski, M; Trzupek, A; Tsang, K W; Tseng, J C-L; Tsiareshka, P V; Tsipolitis, G; Tsirintanis, N; Tsiskaridze, S; Tsiskaridze, V; Tskhadadze, E G; Tsui, K M; Tsukerman, I I; Tsulaia, V; Tsuno, S; Tsybychev, D; Tu, Y; Tudorache, A; Tudorache, V; Tulbure, T T; Tuna, A N; Tupputi, S A; Turchikhin, S; Turgeman, D; Turk Cakir, I; Turra, R; Tuts, P M; Ucchielli, G; Ueda, I; Ughetto, M; Ukegawa, F; Unal, G; Undrus, A; Unel, G; Ungaro, F C; Unno, Y; Unverdorben, C; Urban, J; Urquijo, P; Urrejola, P; Usai, G; Usui, J; Vacavant, L; Vacek, V; Vachon, B; Valderanis, C; Valdes Santurio, E; Valentinetti, S; Valero, A; Valéry, L; Valkar, S; Vallier, A; Valls Ferrer, J A; Van Den Wollenberg, W; van der Graaf, H; van Gemmeren, P; Van Nieuwkoop, J; van Vulpen, I; van Woerden, M C; Vanadia, M; Vandelli, W; Vaniachine, A; Vankov, P; Vardanyan, G; Vari, R; Varnes, E W; Varni, C; Varol, T; Varouchas, D; Vartapetian, A; Varvell, K E; Vasquez, J G; Vasquez, G A; Vazeille, F; Vazquez Schroeder, T; Veatch, J; Veeraraghavan, V; Veloce, L M; Veloso, F; Veneziano, S; Ventura, A; Venturi, M; Venturi, N; Venturini, A; Vercesi, V; Verducci, M; Verkerke, W; Vermeulen, A T; Vermeulen, J C; Vetterli, M C; Viaux Maira, N; Viazlo, O; Vichou, I; Vickey, T; Vickey Boeriu, O E; Viehhauser, G H A; Viel, S; Vigani, L; Villa, M; Villaplana Perez, M; Vilucchi, E; Vincter, M G; Vinogradov, V B; Vishwakarma, A; Vittori, C; Vivarelli, I; Vlachos, S; Vlasak, M; Vogel, M; Vokac, P; Volpi, G; von der Schmitt, H; von Toerne, E; Vorobel, V; Vorobev, K; Vos, M; Voss, R; Vossebeld, J H; Vranjes, N; Vranjes Milosavljevic, M; Vrba, V; Vreeswijk, M; Vuillermet, R; Vukotic, I; Wagner, P; Wagner, W; Wagner-Kuhr, J; Wahlberg, H; Wahrmund, S; Wakabayashi, J; Walder, J; Walker, R; Walkowiak, W; Wallangen, V; Wang, C; Wang, C; Wang, F; Wang, H; Wang, H; Wang, J; Wang, J; Wang, Q; Wang, R; Wang, S M; Wang, T; Wang, W; Wang, W; Wang, Z; Wanotayaroj, C; Warburton, A; Ward, C P; Wardrope, D R; Washbrook, A; Watkins, P M; Watson, A T; Watson, M F; Watts, G; Watts, S; Waugh, B M; Webb, A F; Webb, S; Weber, M S; Weber, S W; Weber, S A; Webster, J S; Weidberg, A R; Weinert, B; Weingarten, J; Weirich, M; Weiser, C; Weits, H; Wells, P S; Wenaus, T; Wengler, T; Wenig, S; Wermes, N; Werner, M D; Werner, P; Wessels, M; Whalen, K; Whallon, N L; Wharton, A M; White, A S; White, A; White, M J; White, R; Whiteson, D; Whitmore, B W; Wickens, F J; Wiedenmann, W; Wielers, M; Wiglesworth, C; Wiik-Fuchs, L A M; Wildauer, A; Wilk, F; Wilkens, H G; Williams, H H; Williams, S; Willis, C; Willocq, S; Wilson, J A; Wingerter-Seez, I; Winkels, E; Winklmeier, F; Winston, O J; Winter, B T; Wittgen, M; Wobisch, M; Wolf, T M H; Wolff, R; Wolter, M W; Wolters, H; Wong, V W S; Worm, S D; Wosiek, B K; Wotschack, J; Wozniak, K W; Wu, M; Wu, S L; Wu, X; Wu, Y; Wyatt, T R; Wynne, B M; Xella, S; Xi, Z; Xia, L; Xu, D; Xu, L; Yabsley, B; Yacoob, S; Yamaguchi, D; Yamaguchi, Y; Yamamoto, A; Yamamoto, S; Yamanaka, T; Yamatani, M; Yamauchi, K; Yamazaki, Y; Yan, Z; Yang, H; Yang, H; Yang, Y; Yang, Z; Yao, W-M; Yap, Y C; Yasu, Y; Yatsenko, E; Yau Wong, K H; Ye, J; Ye, S; Yeletskikh, I; Yigitbasi, E; Yildirim, E; Yorita, K; Yoshihara, K; Young, C; Young, C J S; Yu, J; Yu, J; Yuen, S P Y; Yusuff, I; Zabinski, B; Zacharis, G; Zaidan, R; Zaitsev, A M; Zakharchuk, N; Zalieckas, J; Zaman, A; Zambito, S; Zanzi, D; Zeitnitz, C; Zemla, A; Zeng, J C; Zeng, Q; Zenin, O; Ženiš, T; Zerwas, D; Zhang, D; Zhang, F; Zhang, G; Zhang, H; Zhang, J; Zhang, L; Zhang, L; Zhang, M; Zhang, P; Zhang, R; Zhang, R; Zhang, X; Zhang, Y; Zhang, Z; Zhao, X; Zhao, Y; Zhao, Z; Zhemchugov, A; Zhou, B; Zhou, C; Zhou, L; Zhou, M; Zhou, M; Zhou, N; Zhu, C G; Zhu, H; Zhu, J; Zhu, Y; Zhuang, X; Zhukov, K; Zibell, A; Zieminska, D; Zimine, N I; Zimmermann, C; Zimmermann, S; Zinonos, Z; Zinser, M; Ziolkowski, M; Živković, L; Zobernig, G; Zoccoli, A; Zou, R; Zur Nedden, M; Zwalinski, L
2017-01-01
Results of a search for physics beyond the Standard Model in events containing an energetic photon and large missing transverse momentum with the ATLAS detector at the Large Hadron Collider are reported. As the number of events observed in data, corresponding to an integrated luminosity of 36.1 fb[Formula: see text] of proton-proton collisions at a centre-of-mass energy of [Formula: see text], is in agreement with the Standard Model expectations, model-independent limits are set on the fiducial cross section for the production of events in this final state. Exclusion limits are also placed in models where dark-matter candidates are pair-produced. For dark-matter production via an axial-vector or a vector mediator in the s -channel, this search excludes mediator masses below 750-[Formula: see text] for dark-matter candidate masses below 230-[Formula: see text] at 95% confidence level, depending on the couplings. In an effective theory of dark-matter production, the limits restrict the value of the suppression scale [Formula: see text] to be above [Formula: see text] at 95% confidence level. A limit is also reported on the production of a high-mass scalar resonance by processes beyond the Standard Model, in which the resonance decays to [Formula: see text] and the Z boson subsequently decays into neutrinos.
Modified Parameters of Harmony Search Algorithm for Better Searching
Farraliza Mansor, Nur; Abal Abas, Zuraida; Samad Shibghatullah, Abdul; Rahman, Ahmad Fadzli Nizam Abdul
2017-08-01
The scheduling and rostering problems are deliberated as integrated due to they depend on each other whereby the input of rostering problems is a scheduling problems. In this research, the integrated scheduling and rostering bus driver problems are defined as maximising the balance of the assignment of tasks in term of distribution of shifts and routes. It is essential to achieve is fairer among driver because this can bring to increase in driver levels of satisfaction. The latest approaches still unable to address the fairness problem that has emerged, thus this research proposes a strategy to adopt an amendment of a harmony search algorithm in order to address the fairness issue and thus the level of fairness will be escalate. The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems. In this respect, the three main operators in HS, namely the Harmony Memory Consideration Rate (HMCR), Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing local exploitation and global exploration. These parameters influence the overall performance of the HS algorithm, and therefore it is crucial to fine-tune them. The contributions to this research are the HMCR parameter using step function while the fret spacing concept on guitars that is associated with mathematical formulae is also applied in the BW parameter. The model of constant step function is introduced in the alteration of HMCR parameter. The experimental results revealed that our proposed approach is superior than parameter adaptive harmony search algorithm. In conclusion, this proposed approach managed to generate a fairer roster and was thus capable of maximising the balancing distribution of shifts and routes among drivers, which contributed to the lowering of illness, incidents, absenteeism and accidents.
NATO Advanced Research Institute on Search Theory and Applications
Stone, Lawrence
1980-01-01
The NATO Advanced Research Institute on Search Theory and Appli cations was held at the Hotel Algarve in Praia Da Rocha, Portugal, from March 26 through March 30, 1979, and was sponsored by the NATO Special Programme Panel on Systems Science. There were forty-one participants representing a wide range of backgrounds and interests. The purpose of the institute was to bring together people working in search theory and applications with potential users of search techniques to stimulate the increased application of recent ly developed search technology to civilian problems such as search and rescue, mineral exploration, surveillance, and fishing. Con versely, it was felt that by exposing search analysts to potential applications and new problems, they would be stimulated to develop new techniques for these applications and problems. The exchange of ideas and problems necessary to accomplish these goals was provided in the meeting workshops. There were three workshops, Search and Rescue, Exploration, and Sur...
... Staying Safe Videos for Educators Search English Español Speech Problems KidsHealth / For Teens / Speech Problems What's in ... a person's ability to speak clearly. Some Common Speech and Language Disorders Stuttering is a problem that ...
Directory of Open Access Journals (Sweden)
Salomeh Keyhani
Full Text Available The harmful effects of marijuana on health and in particular cardiovascular health are understudied. To develop such knowledge, an efficient method of developing an informative cohort of marijuana users and non-users is needed.We identified patients with a diagnosis of coronary artery disease using ICD-9 codes who were seen in the San Francisco VA in 2015. We imported these patients' medical record notes into an informatics platform that facilitated text searches. We categorized patients into those with evidence of marijuana use in the past 12 months and patients with no such evidence, using the following text strings: "marijuana", "mjx", and "cannabis". We randomly selected 51 users and 51 non-users based on this preliminary classification, and sent a recruitment letter to 97 of these patients who had contact information available. Patients were interviewed on marijuana use and domains related to cardiovascular health. Data on marijuana use collected from the medical record was compared to data collected as part of the interview.The interview completion rate was 71%. Among the 35 patients identified by text strings as having used marijuana in the previous year, 15 had used marijuana in the past 30 days (positive predictive value = 42.9%. The probability of use in the past month increased from 8.8% to 42.9% in people who have these keywords in their medical record compared to those who did not have these terms in their medical record.Methods that combine text search strategies for participant recruitment with health interviews provide an efficient approach to developing prospective cohorts that can be used to study the health effects of marijuana.
Levy flights and random searches
Energy Technology Data Exchange (ETDEWEB)
Raposo, E P [Laboratorio de Fisica Teorica e Computacional, Departamento de Fisica, Universidade Federal de Pernambuco, Recife-PE, 50670-901 (Brazil); Buldyrev, S V [Department of Physics, Yeshiva University, New York, 10033 (United States); Da Luz, M G E [Departamento de Fisica, Universidade Federal do Parana, Curitiba-PR, 81531-990 (Brazil); Viswanathan, G M [Instituto de Fisica, Universidade Federal de Alagoas, Maceio-AL, 57072-970 (Brazil); Stanley, H E [Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215 (United States)
2009-10-30
In this work we discuss some recent contributions to the random search problem. Our analysis includes superdiffusive Levy processes and correlated random walks in several regimes of target site density, mobility and revisitability. We present results in the context of mean-field-like and closed-form average calculations, as well as numerical simulations. We then consider random searches performed in regular lattices and lattices with defects, and we discuss a necessary criterion for distinguishing true superdiffusion from correlated random walk processes. We invoke energy considerations in relation to critical survival states on the edge of extinction, and we analyze the emergence of Levy behavior in deterministic search walks. Finally, we comment on the random search problem in the context of biological foraging.
VisualRank: applying PageRank to large-scale image search.
Jing, Yushi; Baluja, Shumeet
2008-11-01
Because of the relative ease in understanding and processing text, commercial image-search systems often rely on techniques that are largely indistinguishable from text-search. Recently, academic studies have demonstrated the effectiveness of employing image-based features to provide alternative or additional signals. However, it remains uncertain whether such techniques will generalize to a large number of popular web queries, and whether the potential improvement to search quality warrants the additional computational cost. In this work, we cast the image-ranking problem into the task of identifying "authority" nodes on an inferred visual similarity graph and propose VisualRank to analyze the visual link structures among images. The images found to be "authorities" are chosen as those that answer the image-queries well. To understand the performance of such an approach in a real system, we conducted a series of large-scale experiments based on the task of retrieving images for 2000 of the most popular products queries. Our experimental results show significant improvement, in terms of user satisfaction and relevancy, in comparison to the most recent Google Image Search results. Maintaining modest computational cost is vital to ensuring that this procedure can be used in practice; we describe the techniques required to make this system practical for large scale deployment in commercial search engines.
Block Architecture Problem with Depth First Search Solution and Its Application
Rahim, Robbi; Abdullah, Dahlan; Simarmata, Janner; Pranolo, Andri; Saleh Ahmar, Ansari; Hidayat, Rahmat; Napitupulu, Darmawan; Nurdiyanto, Heri; Febriadi, Bayu; Zamzami, Z.
2018-01-01
Searching is a common process performed by many computer users, Raita algorithm is one algorithm that can be used to match and find information in accordance with the patterns entered. Raita algorithm applied to the file search application using java programming language and the results obtained from the testing process of the file search quickly and with accurate results and support many data types.
Directory of Open Access Journals (Sweden)
Alireza Isfandiyari Moghadam
2010-03-01
Full Text Available The present investigation concerns evaluation, comparison and analysis of search options existing within web-based meta-search engines. 64 meta-search engines were identified. 19 meta-search engines that were free, accessible and compatible with the objectives of the present study were selected. An author’s constructed check list was used for data collection. Findings indicated that all meta-search engines studied used the AND operator, phrase search, number of results displayed setting, previous search query storage and help tutorials. Nevertheless, none of them demonstrated any search options for hypertext searching and displaying the size of the pages searched. 94.7% support features such as truncation, keywords in title and URL search and text summary display. The checklist used in the study could serve as a model for investigating search options in search engines, digital libraries and other internet search tools.
Giuliani, Matteo; Mason, Emanuele; Castelletti, Andrea; Pianosi, Francesca
2014-05-01
The optimal operation of water resources systems is a wide and challenging problem due to non-linearities in the model and the objectives, high dimensional state-control space, and strong uncertainties in the hydroclimatic regimes. The application of classical optimization techniques (e.g., SDP, Q-learning, gradient descent-based algorithms) is strongly limited by the dimensionality of the system and by the presence of multiple, conflicting objectives. This study presents a novel approach which combines Direct Policy Search (DPS) and Multi-Objective Evolutionary Algorithms (MOEAs) to solve high-dimensional state and control space problems involving multiple objectives. DPS, also known as parameterization-simulation-optimization in the water resources literature, is a simulation-based approach where the reservoir operating policy is first parameterized within a given family of functions and, then, the parameters optimized with respect to the objectives of the management problem. The selection of a suitable class of functions to which the operating policy belong to is a key step, as it might restrict the search for the optimal policy to a subspace of the decision space that does not include the optimal solution. In the water reservoir literature, a number of classes have been proposed. However, many of these rules are based largely on empirical or experimental successes and they were designed mostly via simulation and for single-purpose reservoirs. In a multi-objective context similar rules can not easily inferred from the experience and the use of universal function approximators is generally preferred. In this work, we comparatively analyze two among the most common universal approximators: artificial neural networks (ANN) and radial basis functions (RBF) under different problem settings to estimate their scalability and flexibility in dealing with more and more complex problems. The multi-purpose HoaBinh water reservoir in Vietnam, accounting for hydropower
An Enhanced Genetic Algorithm for the Generalized Traveling Salesman Problem
Directory of Open Access Journals (Sweden)
H. Jafarzadeh
2017-12-01
Full Text Available The generalized traveling salesman problem (GTSP deals with finding the minimum-cost tour in a clustered set of cities. In this problem, the traveler is interested in finding the best path that goes through all clusters. As this problem is NP-hard, implementing a metaheuristic algorithm to solve the large scale problems is inevitable. The performance of these algorithms can be intensively promoted by other heuristic algorithms. In this study, a search method is developed that improves the quality of the solutions and competition time considerably in comparison with Genetic Algorithm. In the proposed algorithm, the genetic algorithms with the Nearest Neighbor Search (NNS are combined and a heuristic mutation operator is applied. According to the experimental results on a set of standard test problems with symmetric distances, the proposed algorithm finds the best solutions in most cases with the least computational time. The proposed algorithm is highly competitive with the published until now algorithms in both solution quality and running time.
ARSTEC, Nonlinear Optimization Program Using Random Search Method
International Nuclear Information System (INIS)
Rasmuson, D. M.; Marshall, N. H.
1979-01-01
1 - Description of problem or function: The ARSTEC program was written to solve nonlinear, mixed integer, optimization problems. An example of such a problem in the nuclear industry is the allocation of redundant parts in the design of a nuclear power plant to minimize plant unavailability. 2 - Method of solution: The technique used in ARSTEC is the adaptive random search method. The search is started from an arbitrary point in the search region and every time a point that improves the objective function is found, the search region is centered at that new point. 3 - Restrictions on the complexity of the problem: Presently, the maximum number of independent variables allowed is 10. This can be changed by increasing the dimension of the arrays
Fast and accurate protein substructure searching with simulated annealing and GPUs
Directory of Open Access Journals (Sweden)
Stivala Alex D
2010-09-01
Full Text Available Abstract Background Searching a database of protein structures for matches to a query structure, or occurrences of a structural motif, is an important task in structural biology and bioinformatics. While there are many existing methods for structural similarity searching, faster and more accurate approaches are still required, and few current methods are capable of substructure (motif searching. Results We developed an improved heuristic for tableau-based protein structure and substructure searching using simulated annealing, that is as fast or faster and comparable in accuracy, with some widely used existing methods. Furthermore, we created a parallel implementation on a modern graphics processing unit (GPU. Conclusions The GPU implementation achieves up to 34 times speedup over the CPU implementation of tableau-based structure search with simulated annealing, making it one of the fastest available methods. To the best of our knowledge, this is the first application of a GPU to the protein structural search problem.
Directory of Open Access Journals (Sweden)
Antonio Roberto Balbo
2012-01-01
Full Text Available This paper proposes a predictor-corrector primal-dual interior point method which introduces line search procedures (IPLS in both the predictor and corrector steps. The Fibonacci search technique is used in the predictor step, while an Armijo line search is used in the corrector step. The method is developed for application to the economic dispatch (ED problem studied in the field of power systems analysis. The theory of the method is examined for quadratic programming problems and involves the analysis of iterative schemes, computational implementation, and issues concerning the adaptation of the proposed algorithm to solve ED problems. Numerical results are presented, which demonstrate improvements and the efficiency of the IPLS method when compared to several other methods described in the literature. Finally, postoptimization analyses are performed for the solution of ED problems.
Reactive power planning with FACTS devices using gravitational search algorithm
Directory of Open Access Journals (Sweden)
Biplab Bhattacharyya
2015-09-01
Full Text Available In this paper, Gravitational Search Algorithm (GSA is used as optimization method in reactive power planning using FACTS (Flexible AC transmission system devices. The planning problem is formulated as a single objective optimization problem where the real power loss and bus voltage deviations are minimized under different loading conditions. GSA based optimization algorithm and particle swarm optimization techniques (PSO are applied on IEEE 30 bus system. Results show that GSA can also be a very effective tool for reactive power planning.
Constraint-based solver for the Military unit path finding problem
CSIR Research Space (South Africa)
Leenen, L
2010-04-01
Full Text Available -based approach because it requires flexibility in modelling. The authors formulate the MUPFP as a constraint satisfaction problem and a constraint-based extension of the search algorithm. The concept demonstrator uses a provided map, for example taken from Google...
Searching in the Context of a Task: A Review of Methods and Tools
Directory of Open Access Journals (Sweden)
Ana Maguitman
2018-04-01
Full Text Available Contextual information extracted from the user task can help to better target retrieval to task-relevant content. In particular, topical context can be exploited to identify the subject of the information needs, contributing to reduce the information overload problem. A great number of methods exist to extract raw context data and contextual interaction patterns from the user task and to model this information using higher-level representations. Context can then be used as a source for automatic query generation, or as a means to refine or disambiguate user-generated queries. It can also be used to filter and rank results as well as to select domain-specific search engines with better capabilities to satisfy specific information requests. This article reviews methods that have been applied to deal with the problem of reflecting the current and long-term interests of a user in the search process. It discusses major difficulties encountered in the research area of context-based information retrieval and presents an overview of tools proposed since the mid-nineties to deal with the problem of context-based search.
Directory of Open Access Journals (Sweden)
Mahdi Alinaghian
2017-01-01
Full Text Available In this paper, an uncertain integrated model for simultaneously locating temporary health centers in the affected areas, allocating affected areas to these centers, and routing to transport their required good is considered. Health centers can be settled in one of the affected areas or in a place out of them; therefore, the proposed model offers the best relief operation policy when it is possible to supply the goods of affected areas (which are customers of goods directly or under coverage. Due to that the problem is NP-Hard, to solve the problem in large-scale, a meta-heuristic algorithm based on harmony search algorithm is presented and its performance has been compared with basic harmony search algorithm and neighborhood search algorithm in small and large scale test problems. The results show that the proposed harmony search algorithm has a suitable efficiency.
Top-k Keyword Search Over Graphs Based On Backward Search
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Zeng Jia-Hui
2017-01-01
Full Text Available Keyword search is one of the most friendly and intuitive information retrieval methods. Using the keyword search to get the connected subgraph has a lot of application in the graph-based cognitive computation, and it is a basic technology. This paper focuses on the top-k keyword searching over graphs. We implemented a keyword search algorithm which applies the backward search idea. The algorithm locates the keyword vertices firstly, and then applies backward search to find rooted trees that contain query keywords. The experiment shows that query time is affected by the iteration number of the algorithm.
Directory of Open Access Journals (Sweden)
Salvator Abreu
2009-10-01
Full Text Available We explore the use of the Cell Broadband Engine (Cell/BE for short for combinatorial optimization applications: we present a parallel version of a constraint-based local search algorithm that has been implemented on a multiprocessor BladeCenter machine with twin Cell/BE processors (total of 16 SPUs per blade. This algorithm was chosen because it fits very well the Cell/BE architecture and requires neither shared memory nor communication between processors, while retaining a compact memory footprint. We study the performance on several large optimization benchmarks and show that this achieves mostly linear time speedups, even sometimes super-linear. This is possible because the parallel implementation might explore simultaneously different parts of the search space and therefore converge faster towards the best sub-space and thus towards a solution. Besides getting speedups, the resulting times exhibit a much smaller variance, which benefits applications where a timely reply is critical.
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Vuković Slobodan
2007-01-01
Full Text Available Topic of the article is problem of trust in judiciary as a most important part of legal system. For all empirical researches so far have shown very law degree of this trust many authors were searching for the causes of this phenomenon. Among multifold causes some are special worth while to be mentioned here: historical inheritance, political pressures, delaying of judiciary decisions, respect of the laws, transferring of responsibility from political power to the judiciary, public comments of judiciary decisions, media pressures, efficiency of judiciary and police. Among inner factors author pays attention to competency of judges, modes of penal policy, modes of judges’ entitlement, problems of communication, involvement into criminal and corruptional affairs, etc.
Directory of Open Access Journals (Sweden)
Muchammad Abrori
2015-10-01
Full Text Available Yogyakarta offers many tourist attractions, from nature based tourism, culinary tourism until cultural tourism. With so many tourist attractions offered by Yogyakarta, tourist often finds it difficult to arrange their travel schedule (from choosing which tourist attractions to be visited until choosing which route tourist should takes to maximize their vacation time. Therefore, it’s required to have a way to determine the shortest tour route so tourist can make their tour in the Yogyakarta effective. This problem can be categorized as Traveling Salesman Problem (TSP case. There are a lot of methods can be used to find the shortest route in Travelling Salesman Problems (TSP case. To solve the problem, which is to find the shortest tour route in Yogyakarta, Algorithm Best-First Travelling will be used in this undergraduate thesis. The implementation of Algorithm Best-First Search to find the shortest tour route in Yogyakarta can be used to produce a solution for tourist to choose the shortest tour package and decide which route they should take. The premium tour package produces tour route from Adi Sucipto Airport-Gembira Loka Zoo- Purawisata-N’dalem Gamelan Hotel-Yogyakarta Palace-Benteng Vredeburg Museum-Taman Pintar-Tamansari-Adi Sucipto Airport with distance covered 20.297 meter. The middle tour package produces tour route from Tugu railway station-Benteng Vredeburg Museum- Taman Pintar-Yogyakarta Palace-Mawar Asri Hotel-Tamansari-Purawisata-Gembira Loka Zoo-Tugu railway station with distance covered 11.772 meter. The economy tour package produces tour route from Giwangan bus station- Gembira Loka zoo-Purawisata-Yogyakarta Palace-Mitra Hotel-Benteng Vredeburg Museum-Taman Pintar-Tamansari-Giwangan bus station with distance covered 14.037 meter.
Kaplan, Craig A.; Simon, Herbert A.
1990-01-01
Attaining the insight needed to solve the Mutilated Checkerboard problem, which requires discovery of an effective problem representation (EPR), is described. Performance on insight problems can be predicted from the availability of generators and constraints in the search for an EPR. Data for 23 undergraduates were analyzed. (TJH)
SOCIAL NETWORK OPTIMIZATION A NEW METHAHEURISTIC FOR GENERAL OPTIMIZATION PROBLEMS
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Hassan Sherafat
2017-12-01
Full Text Available In the recent years metaheuristics were studied and developed as powerful technics for hard optimization problems. Some of well-known technics in this field are: Genetic Algorithms, Tabu Search, Simulated Annealing, Ant Colony Optimization, and Swarm Intelligence, which are applied successfully to many complex optimization problems. In this paper, we introduce a new metaheuristic for solving such problems based on social networks concept, named as Social Network Optimization – SNO. We show that a wide range of np-hard optimization problems may be solved by SNO.
A HYBRID HEURISTIC ALGORITHM FOR SOLVING THE RESOURCE CONSTRAINED PROJECT SCHEDULING PROBLEM (RCPSP
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Juan Carlos Rivera
Full Text Available The Resource Constrained Project Scheduling Problem (RCPSP is a problem of great interest for the scientific community because it belongs to the class of NP-Hard problems and no methods are known that can solve it accurately in polynomial processing times. For this reason heuristic methods are used to solve it in an efficient way though there is no guarantee that an optimal solution can be obtained. This research presents a hybrid heuristic search algorithm to solve the RCPSP efficiently, combining elements of the heuristic Greedy Randomized Adaptive Search Procedure (GRASP, Scatter Search and Justification. The efficiency obtained is measured taking into account the presence of the new elements added to the GRASP algorithm taken as base: Justification and Scatter Search. The algorithms are evaluated using three data bases of instances of the problem: 480 instances of 30 activities, 480 of 60, and 600 of 120 activities respectively, taken from the library PSPLIB available online. The solutions obtained by the developed algorithm for the instances of 30, 60 and 120 are compared with results obtained by other researchers at international level, where a prominent place is obtained, according to Chen (2011.
Mathematical programming solver based on local search
Gardi, Frédéric; Darlay, Julien; Estellon, Bertrand; Megel, Romain
2014-01-01
This book covers local search for combinatorial optimization and its extension to mixed-variable optimization. Although not yet understood from the theoretical point of view, local search is the paradigm of choice for tackling large-scale real-life optimization problems. Today's end-users demand interactivity with decision support systems. For optimization software, this means obtaining good-quality solutions quickly. Fast iterative improvement methods, like local search, are suited to satisfying such needs. Here the authors show local search in a new light, in particular presenting a new kind of mathematical programming solver, namely LocalSolver, based on neighborhood search. First, an iconoclast methodology is presented to design and engineer local search algorithms. The authors' concern about industrializing local search approaches is of particular interest for practitioners. This methodology is applied to solve two industrial problems with high economic stakes. Software based on local search induces ex...
Current problems of teaching spelling in the first cycle of Primary Education
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Martha Valcárcel González
2005-12-01
Full Text Available This article presents from the theoretical point of view the spelling problem as one of the main difficulties that there is in Primary Education and in which teachers intensively work searching for solutions.
DEFF Research Database (Denmark)
2006-01-01
Sound search is provided by the major search engines, however, indexing is text based, not sound based. We will establish a dedicated sound search services with based on sound feature indexing. The current demo shows the concept of the sound search engine. The first engine will be realased June...
International Nuclear Information System (INIS)
Savic, Dobrica
2014-01-01
Google Search has established a new standard for information retrieval which did not exist with previous generations of library search facilities. The INIS hosts one of the world’s largest collections of published information on the peaceful uses of nuclear science and technology. It offers on-line access to a unique collection of 3.6 million bibliographic records and 483,000 full texts of non-conventional (grey) literature. This large digital library collection suffered from most of the well-known shortcomings of the classic library catalogue. Searching was complex and complicated, it required training in Boolean logic, full-text searching was not an option, and response time was slow. An opportune moment to improve the system came with the retirement of the previous catalogue software and the adoption of GSA as an organization-wide search engine standard. INIS was quick to realize the potential of using such a well-known application to replace its on-line catalogue. This paper presents the advantages and disadvantages encountered during three years of GSA use. Based on specific INIS-based practice and experience, this paper also offers some guidelines on ways to improve classic collections of millions of bibliographic and full-text documents, while reaping multiple benefits, such as increased use, accessibility, usability, expandability and improving user search and retrieval experiences. (author)
Harmony Search Method: Theory and Applications
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X. Z. Gao
2015-01-01
Full Text Available The Harmony Search (HS method is an emerging metaheuristic optimization algorithm, which has been employed to cope with numerous challenging tasks during the past decade. In this paper, the essential theory and applications of the HS algorithm are first described and reviewed. Several typical variants of the original HS are next briefly explained. As an example of case study, a modified HS method inspired by the idea of Pareto-dominance-based ranking is also presented. It is further applied to handle a practical wind generator optimal design problem.
Energy Technology Data Exchange (ETDEWEB)
Souza Filho, Erito M.; Bahiense, Laura; Ferreira Filho, Virgilio J.M. [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia (COPPE); Lima, Leonardo [Centro Federal de Educacao Tecnologica Celso Sukow da Fonseca (CEFET-RJ), Rio de Janeiro, RJ (Brazil)
2008-07-01
Pipeline are known as the most reliable and economical mode of transportation for petroleum and its derivatives, especially when large amounts of products have to be pumped for large distances. In this work we address the short-term schedule of a pipeline system comprising the distribution of several petroleum derivatives from a single oil refinery to several depots, connected to local consumer markets, through a single multi-product pipeline. We propose an integer linear programming formulation and a variable neighborhood search meta-heuristic in order to compare the performances of the exact and heuristic approaches to the problem. Computational tests in C language and MOSEL/XPRESS-MP language are performed over a real Brazilian pipeline system. (author)
Visual search of illusory contours: Shape and orientation effects
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Gvozdenović Vasilije
2008-01-01
Full Text Available Illusory contours are specific class of visual stimuli that represent stimuli configurations perceived as integral irrespective of the fact that they are given in fragmented uncompleted wholes. Due to their specific features, illusory contours gained much attention in last decade representing prototype of stimuli used in investigations focused on binding problem. On the other side, investigations of illusory contours are related to problem of the level of their visual processing. Neurophysiologic studies show that processing of illusory contours proceed relatively early, on the V2 level, on the other hand most of experimental studies claim that illusory contours are perceived with engagement of visual attention, binding their elements to whole percept. This research is focused on two experiments in which visual search of illusory contours are based on shape and orientation. The main experimental procedure evolved the task proposed by Bravo and Nakayama where instead of detection, subjects were performing identification of one among two possible targets. In the first experiment subjects detected the presence of illusory square or illusory triangle, while in the second experiment subject were detecting two different orientations of illusory triangle. The results are interpreted in terms of visual search and feature integration theory. Beside the type of visual search task, search type proved to be dependent of specific features of illusory shapes which further complicate theoretical interpretation of the level of their perception.
Problems of reducing the exhaustive search
Kreinovich, V
1996-01-01
This collection contains translations of papers on propositional satisfiability and related logical problems which appeared in Problemy Sokrashcheniya Perebora, published in Russian in 1987 by the Scientific Council "Cybernetics" of the USSR Academy of Sciences. The problems form the nucleus of this intensively developing area. This translation is dedicated to the memory of two remarkable Russian mathematicians, Sergei Maslov and his wife, Nina Maslova. Maslov is known as the originator of the inverse method in automated deduction, which was discovered at the same time as the resolution method
Ershad Sarabi, Roghayeh; Sadoughi, Farahnaz; Jamshidi Orak, Roohangiz; Bahaadinbeigy, Kambiz
2016-01-01
Context Medication non-adherence is a commonly observed problem in the self-administration of treatment, regardless of the disease type. Text messaging reminders, as electronic reminders, provide an opportunity to improve medication adherence. In this study, we aimed to provide evidence addressing the question of whether text message reminders were effective in improving patients? adherence to medication. Evidence Acquisition We carried out a systematic literature search, using the five elect...
A heuristic algorithm for a multi-product four-layer capacitated location-routing problem
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Mohsen Hamidi
2014-01-01
Full Text Available The purpose of this study is to solve a complex multi-product four-layer capacitated location-routing problem (LRP in which two specific constraints are taken into account: 1 plants have limited production capacity, and 2 central depots have limited capacity for storing and transshipping products. The LRP represents a multi-product four-layer distribution network that consists of plants, central depots, regional depots, and customers. A heuristic algorithm is developed to solve the four-layer LRP. The heuristic uses GRASP (Greedy Randomized Adaptive Search Procedure and two probabilistic tabu search strategies of intensification and diversification to tackle the problem. Results show that the heuristic solves the problem effectively.
Searching for Bill and Jane: Electronic Full-Text Literature.
Still, Julie; Kassabian, Vibiana
1998-01-01
Examines electronic full-text literature available on the World Wide Web and on CD-ROM. Discusses authors and genres, electronic texts, and fees. Highlights Shakespeare, Jane Austen, and nature writing. Provides a bibliography of Web guides, specialized Shakespeare pages, and pages dealing with the Shakespeare authorship debate and secondary…
Diversification in an image retrieval system based on text and image processing
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Adrian Iftene
2014-11-01
Full Text Available In this paper we present an image retrieval system created within the research project MUCKE (Multimedia and User Credibility Knowledge Extraction, a CHIST-ERA research project where UAIC{\\footnote{"Alexandru Ioan Cuza" University of Iasi}} is one of the partners{\\footnote{Together with Technical University from Wienna, Austria, CEA-LIST Institute from Paris, France and BILKENT University from Ankara, Turkey}}. Our discussion in this work will focus mainly on components that are part of our image retrieval system proposed in MUCKE, and we present the work done by the UAIC group. MUCKE incorporates modules for processing multimedia content in different modes and languages (like English, French, German and Romanian and UAIC is responsible with text processing tasks (for Romanian and English. One of the problems addressed by our work is related to search results diversification. In order to solve this problem, we first process the user queries in both languages and secondly, we create clusters of similar images.
A Quantitative Method for Localizing User Interface Problems: The D-TEO Method
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Juha Lamminen
2009-01-01
Full Text Available A large array of evaluation methods have been proposed to identify Website usability problems. In log-based evaluation, information about the performance of users is collected and stored into log files, and used to find problems and deficiencies in Web page designs. Most methods require the programming and modeling of large task models, which are cumbersome processes for evaluators. Also, because much statistical data is collected onto log files, recognizing which Web pages require deeper usability analysis is difficult. This paper suggests a novel quantitative method, called the D-TEO, for locating problematic Web pages. This semiautomated method explores the decomposition of interaction tasks of directed information search into elementary operations, deploying two quantitative usability criteria, search success and search time, to reveal how a user navigates within a web of hypertext.
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Jun-qing Li
2014-01-01
Full Text Available A hybrid algorithm which combines particle swarm optimization (PSO and iterated local search (ILS is proposed for solving the hybrid flowshop scheduling (HFS problem with preventive maintenance (PM activities. In the proposed algorithm, different crossover operators and mutation operators are investigated. In addition, an efficient multiple insert mutation operator is developed for enhancing the searching ability of the algorithm. Furthermore, an ILS-based local search procedure is embedded in the algorithm to improve the exploitation ability of the proposed algorithm. The detailed experimental parameter for the canonical PSO is tuning. The proposed algorithm is tested on the variation of 77 Carlier and Néron’s benchmark problems. Detailed comparisons with the present efficient algorithms, including hGA, ILS, PSO, and IG, verify the efficiency and effectiveness of the proposed algorithm.
Heuristic for Solving the Multiple Alignment Sequence Problem
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Roman Anselmo Mora Gutiérrez
2011-03-01
Full Text Available In this paper we developed a new algorithm for solving the problem of multiple sequence alignment (AM S, which is a hybrid metaheuristic based on harmony search and simulated annealing. The hybrid was validated with the methodology of Julie Thompson. This is a basic algorithm and and results obtained during this stage are encouraging.
Accelerated Simplified Swarm Optimization with Exploitation Search Scheme for Data Clustering.
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Wei-Chang Yeh
Full Text Available Data clustering is commonly employed in many disciplines. The aim of clustering is to partition a set of data into clusters, in which objects within the same cluster are similar and dissimilar to other objects that belong to different clusters. Over the past decade, the evolutionary algorithm has been commonly used to solve clustering problems. This study presents a novel algorithm based on simplified swarm optimization, an emerging population-based stochastic optimization approach with the advantages of simplicity, efficiency, and flexibility. This approach combines variable vibrating search (VVS and rapid centralized strategy (RCS in dealing with clustering problem. VVS is an exploitation search scheme that can refine the quality of solutions by searching the extreme points nearby the global best position. RCS is developed to accelerate the convergence rate of the algorithm by using the arithmetic average. To empirically evaluate the performance of the proposed algorithm, experiments are examined using 12 benchmark datasets, and corresponding results are compared with recent works. Results of statistical analysis indicate that the proposed algorithm is competitive in terms of the quality of solutions.
A Study on the Enhanced Best Performance Algorithm for the Just-in-Time Scheduling Problem
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Sivashan Chetty
2015-01-01
Full Text Available The Just-In-Time (JIT scheduling problem is an important subject of study. It essentially constitutes the problem of scheduling critical business resources in an attempt to optimize given business objectives. This problem is NP-Hard in nature, hence requiring efficient solution techniques. To solve the JIT scheduling problem presented in this study, a new local search metaheuristic algorithm, namely, the enhanced Best Performance Algorithm (eBPA, is introduced. This is part of the initial study of the algorithm for scheduling problems. The current problem setting is the allocation of a large number of jobs required to be scheduled on multiple and identical machines which run in parallel. The due date of a job is characterized by a window frame of time, rather than a specific point in time. The performance of the eBPA is compared against Tabu Search (TS and Simulated Annealing (SA. SA and TS are well-known local search metaheuristic algorithms. The results show the potential of the eBPA as a metaheuristic algorithm.
Problem solving stages in the five square problem.
Fedor, Anna; Szathmáry, Eörs; Öllinger, Michael
2015-01-01
According to the restructuring hypothesis, insight problem solving typically progresses through consecutive stages of search, impasse, insight, and search again for someone, who solves the task. The order of these stages was determined through self-reports of problem solvers and has never been verified behaviorally. We asked whether individual analysis of problem solving attempts of participants revealed the same order of problem solving stages as defined by the theory and whether their subjective feelings corresponded to the problem solving stages they were in. Our participants tried to solve the Five-Square problem in an online task, while we recorded the time and trajectory of their stick movements. After the task they were asked about their feelings related to insight and some of them also had the possibility of reporting impasse while working on the task. We found that the majority of participants did not follow the classic four-stage model of insight, but had more complex sequences of problem solving stages, with search and impasse recurring several times. This means that the classic four-stage model is not sufficient to describe variability on the individual level. We revised the classic model and we provide a new model that can generate all sequences found. Solvers reported insight more often than non-solvers and non-solvers reported impasse more often than solvers, as expected; but participants did not report impasse more often during behaviorally defined impasse stages than during other stages. This shows that impasse reports might be unreliable indicators of impasse. Our study highlights the importance of individual analysis of problem solving behavior to verify insight theory.
The problem of popularisation of expert texts: Analysis of media discourses on Ljubljana urbanism
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Matjaž Uršič
2008-01-01
Full Text Available In the period after the post-socialist transition of Slovenia we can notice an increased number of instrumental, marketing oriented public relation (PR activities in expert and popular media from the field of spatial planning. The problem of instrumentalisation of media discourses reflects in exclusion i.e. deficiency of content-argumentative language in public debate. The basic purpose of the article is to analyse and expose some of the relationships and processes that have great influence in the space of the city and its surroundings. The article draws on empirical evidence from quantitative and qualitative analyse of texts and pays attention to some of the actual cases in spatial planning that show hidden contents, explicit and implicit ideological constructions, particularisms of interest groups and strategies of instrumental marketing campaigns.
Switching strategies to optimize search
International Nuclear Information System (INIS)
Shlesinger, Michael F
2016-01-01
Search strategies are explored when the search time is fixed, success is probabilistic and the estimate for success can diminish with time if there is not a successful result. Under the time constraint the problem is to find the optimal time to switch a search strategy or search location. Several variables are taken into account, including cost, gain, rate of success if a target is present and the probability that a target is present. (paper: interdisciplinary statistical mechanics)
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Muhammad Sulaiman
2018-01-01
Full Text Available This paper presents the solution of directional overcurrent relay (DOCR problems using Simulated Annealing based Symbiotic Organism Search (SASOS. The objective function of the problem is to minimize the sum of the operating times of all primary relays. The DOCR problem is nonlinear and highly constrained with two types of decision variables, namely, the time dial settings (TDS and plug setting (PS. In this paper, three models of the problem are considered, the IEEE 3-bus, 4-bus, and 6-bus, respectively. We have applied SASOS to solve the problem and the obtained results are compared with other algorithms available in the literature.
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Jose Bernal
2017-10-01
Full Text Available Purpose: We consider a real case study of a vehicle routing problem with a heterogeneous fleet and time windows (HFVRPTW for a franchise company bottling Coca-Cola products in Colombia. This study aims to determine the routes to be performed to fulfill the demand of the customers by using a heterogeneous fleet and considering soft time windows. The objective is to minimize the distance traveled by the performed routes. Design/methodology/approach: We propose a two-phase heuristic algorithm. In the proposed approach, after an initial phase (first phase, a granular tabu search is applied during the improvement phase (second phase. Two additional procedures are considered to help that the algorithm could escape from local optimum, given that during a given number of iterations there has been no improvement. Findings: Computational experiments on real instances show that the proposed algorithm is able to obtain high-quality solutions within a short computing time compared to the results found by the software that the company currently uses to plan the daily routes. Originality/value: We propose a novel metaheuristic algorithm for solving a real routing problem by considering heterogeneous fleet and time windows. The efficiency of the proposed approach has been tested on real instances, and the computational experiments shown its applicability and performance for solving NP-Hard Problems related with routing problems with similar characteristics. The proposed algorithm was able to improve some of the current solutions applied by the company by reducing the route length and the number of vehicles.
Using 2-Opt based evolution strategy for travelling salesman problem
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Kenan Karagul
2016-03-01
Full Text Available Harmony search algorithm that matches the (µ+1 evolution strategy, is a heuristic method simulated by the process of music improvisation. In this paper, a harmony search algorithm is directly used for the travelling salesman problem. Instead of conventional selection operators such as roulette wheel, the transformation of real number values of harmony search algorithm to order index of vertex representation and improvement of solutions are obtained by using the 2-Opt local search algorithm. Then, the obtained algorithm is tested on two different parameter groups of TSPLIB. The proposed method is compared with classical 2-Opt which randomly started at each step and best known solutions of test instances from TSPLIB. It is seen that the proposed algorithm offers valuable solutions.
"Free full text articles": where to search for them?
Singh, Ashish; Singh, Manish; Singh, Ajai Kumar; Singh, Deepti; Singh, Pratibha; Sharma, Abhishek
2011-07-01
References form the backbone of any medical literature. Presently, because of high inflation, it is very difficult for any library/organization/college to purchase all journals. The condition is even worse for an individual person, such as private practitioners. The solution lies in the free availability of full-text articles. Here, the authors share their experiences about the accessibility of free full-text articles.
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Arturo Valdivia-Gonzalez
2017-01-01
Full Text Available Recently, many researchers have proved that the electrification of the transport sector is a key for reducing both the emissions of green-house pollutants and the dependence on oil for transportation. As a result, Plug-in Hybrid Electric Vehicles (or PHEVs are receiving never before seen increased attention. Consequently, large-scale penetration of PHEVs into the market is expected to take place in the near future, however, an unattended increase in the PHEVs needs may cause several technical problems which could potentially compromise the stability of power systems. As a result of the growing necessity for addressing such issues, topics related to the optimization of PHEVs’ charging infrastructures have captured the attention of many researchers. Related to this, several state-of-the-art swarm optimization methods (such as the well-known Particle Swarm Optimization (PSO or the recently proposed Gravitational Search Algorithm (GSA approach have been successfully applied in the optimization of the average State of Charge (SoC, which represents one of the most important performance indicators in the context of PHEVs’ intelligent power allocation. Many of these swarm optimization methods, however, are known to be subject to several critical flaws, including premature convergence and a lack of balance between the exploration and exploitation of solutions. Such problems are usually related to the evolutionary operators employed by each of the methods on the exploration and exploitation of new solutions. In this paper, the recently proposed States of Matter Search (SMS swarm optimization method is proposed for maximizing the average State of Charge of PHEVs within a charging station. In our experiments, several different scenarios consisting on different numbers of PHEVs were considered. To test the feasibility of the proposed approach, comparative experiments were performed against other popular PHEVs’ State of Charge maximization approaches
Text Mining the History of Medicine.
Thompson, Paul; Batista-Navarro, Riza Theresa; Kontonatsios, Georgios; Carter, Jacob; Toon, Elizabeth; McNaught, John; Timmermann, Carsten; Worboys, Michael; Ananiadou, Sophia
2016-01-01
Historical text archives constitute a rich and diverse source of information, which is becoming increasingly readily accessible, due to large-scale digitisation efforts. However, it can be difficult for researchers to explore and search such large volumes of data in an efficient manner. Text mining (TM) methods can help, through their ability to recognise various types of semantic information automatically, e.g., instances of concepts (places, medical conditions, drugs, etc.), synonyms/variant forms of concepts, and relationships holding between concepts (which drugs are used to treat which medical conditions, etc.). TM analysis allows search systems to incorporate functionality such as automatic suggestions of synonyms of user-entered query terms, exploration of different concepts mentioned within search results or isolation of documents in which concepts are related in specific ways. However, applying TM methods to historical text can be challenging, according to differences and evolutions in vocabulary, terminology, language structure and style, compared to more modern text. In this article, we present our efforts to overcome the various challenges faced in the semantic analysis of published historical medical text dating back to the mid 19th century. Firstly, we used evidence from diverse historical medical documents from different periods to develop new resources that provide accounts of the multiple, evolving ways in which concepts, their variants and relationships amongst them may be expressed. These resources were employed to support the development of a modular processing pipeline of TM tools for the robust detection of semantic information in historical medical documents with varying characteristics. We applied the pipeline to two large-scale medical document archives covering wide temporal ranges as the basis for the development of a publicly accessible semantically-oriented search system. The novel resources are available for research purposes, while
... Staying Safe Videos for Educators Search English Español Learning Problems KidsHealth / For Kids / Learning Problems What's in ... for how to make it better. What Are Learning Disabilities? Learning disabilities aren't contagious, but they ...
A Hybrid Genetic Algorithm for the Multiple Crossdocks Problem
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Zhaowei Miao
2012-01-01
Full Text Available We study a multiple crossdocks problem with supplier and customer time windows, where any violation of time windows will incur a penalty cost and the flows through the crossdock are constrained by fixed transportation schedules and crossdock capacities. We prove this problem to be NP-hard in the strong sense and therefore focus on developing efficient heuristics. Based on the problem structure, we propose a hybrid genetic algorithm (HGA integrating greedy technique and variable neighborhood search method to solve the problem. Extensive experiments under different scenarios were conducted, and results show that HGA outperforms CPLEX solver, providing solutions in realistic timescales.
Online Patent Searching: The Realities.
Kaback, Stuart M.
1983-01-01
Considers patent subject searching capabilities of major online databases, noting patent claims, "deep-indexed" files, test searches, retrieval of related references, multi-database searching, improvements needed in indexing of chemical structures, full text searching, improvements needed in handling numerical data, and augmenting a…
Directory of Open Access Journals (Sweden)
Lorena Pradenas Rojas
2008-12-01
Full Text Available En este estudio se presenta un modelo matemático para un problema genérico de asignación de personal. Se implementa y evalúa un procedimiento de solución mediante la metaheurística Tabu Search. El algoritmo propuesto es usado para resolver un caso real de asignación de supervisores forestales. Los resultados muestran que el algoritmo desarrollado es eficiente en la resolución de este tipo de problema y tiene un amplio rango de aplicación para otras situaciones reales.This study presents a mathematical model for a generic problem of staff allocation. A solution is implemented and evaluated by means of the Tabu Search metaheuristic. The proposed algorithm is used to solve a real case of forestry supervisors' allocation. The results show that the developed algorithm is efficient solving this kind of problems and that it has a wide range of application for other real situations.
A Genetic Algorithm for Selection of Fixed-Size Subsets with Application to Design Problems
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Mark A. Wolters
2015-11-01
Full Text Available The R function kofnGA conducts a genetic algorithm search for the best subset of k items from a set of n alternatives, given an objective function that measures the quality of a subset. The function fills a gap in the presently available subset selection software, which typically searches over a range of subset sizes, restricts the types of objective functions considered, or does not include freely available code. The new function is demonstrated on two types of problem where a fixed-size subset search is desirable: design of environmental monitoring networks, and D-optimal design of experiments. Additionally, the performance is evaluated on a class of constructed test problems with a novel design that is interesting in its own right.
Adaptive Large Neighbourhood Search
DEFF Research Database (Denmark)
Røpke, Stefan
Large neighborhood search is a metaheuristic that has gained popularity in recent years. The heuristic repeatedly moves from solution to solution by first partially destroying the solution and then repairing it. The best solution observed during this search is presented as the final solution....... This tutorial introduces the large neighborhood search metaheuristic and the variant adaptive large neighborhood search that dynamically tunes parameters of the heuristic while it is running. Both heuristics belong to a broader class of heuristics that are searching a solution space using very large...... neighborhoods. The tutorial also present applications of the adaptive large neighborhood search, mostly related to vehicle routing problems for which the heuristic has been extremely successful. We discuss how the heuristic can be parallelized and thereby take advantage of modern desktop computers...
Directory of Open Access Journals (Sweden)
Dobrica Savic
2014-05-01
The International Nuclear Information System (INIS hosts one of the world’s largest collections of published information on the peaceful uses of nuclear science and technology. It offers online access to a unique collection of 3.6 million bibliographic records and 320,000 full-texts of non-conventional (grey literature. This large digital library collection suffered from most of the well-known shortcomings of the classic library catalogue. Searching was complex and complicated, required some training in using Boolean logic, full-text searching was not an option, and the response time was slow. An opportune moment came with the retirement of the previous catalogue software and with the adoption of Google Search Appliance (GSA as an organization-wide search engine standard. INIS was quick to realize a great potential in using such a well-known application as a replacement for its online catalogue and this paper presents the advantages and disadvantages encountered during three years of GSA use. Based on specific INIS-based practice and experience, this paper also offers some guidelines on ways to improve classic collections of millions of bibliographic and full-text documents, while achieving multiple benefits such as increased use, accessibility, usability, expandability and improving the user search and retrieval experience.
Spatial Indexing for Data Searching in Mobile Sensing Environments
Directory of Open Access Journals (Sweden)
Yuchao Zhou
2017-06-01
Full Text Available Data searching and retrieval is one of the fundamental functionalities in many Web of Things applications, which need to collect, process and analyze huge amounts of sensor stream data. The problem in fact has been well studied for data generated by sensors that are installed at fixed locations; however, challenges emerge along with the popularity of opportunistic sensing applications in which mobile sensors keep reporting observation and measurement data at variable intervals and changing geographical locations. To address these challenges, we develop the Geohash-Grid Tree, a spatial indexing technique specially designed for searching data integrated from heterogeneous sources in a mobile sensing environment. Results of the experiments on a real-world dataset collected from the SmartSantander smart city testbed show that the index structure allows efficient search based on spatial distance, range and time windows in a large time series database.
The provably total search problems of bounded arithmetic
Czech Academy of Sciences Publication Activity Database
Skelley, A.; Thapen, Neil
2011-01-01
Roč. 103, č. 1 (2011), s. 106-138 ISSN 0024-6115 R&D Projects: GA MŠk LC505 Institutional research plan: CEZ:AV0Z10190503 Keywords : Pigeonhole principle * polynomial hierarchy * local search Subject RIV: BA - General Mathematics Impact factor: 1.324, year: 2011 http://plms.oxfordjournals.org/content/103/1/106
Open Search Environments: The Free Alternative to Commercial Search Services
Directory of Open Access Journals (Sweden)
Adrian O'Riordan
2014-06-01
Full Text Available Open search systems present a free and less restricted alternative to commercial search services. This paper explores the space of open search technology looking in particular at the issue of interoperability. A description of current protocols and formats for engineering open search applications is presented. The suitability of these technologies and issues around their adoption and operation are discussed. This open search approach is especially proving a fitting choice in applications involving the harvesting of resources and information integration. Principal among the technological solutions are OpenSearch and SRU. OpenSearch and SRU implement a federated model to enable existing and new search engines and search clients communicate. Applications and instances where Opensearch and SRU can be combined are presented. Other relevant technologies such as OpenURL, Apache Solr, and OAI-PMH are also discussed. The deployment of these freely licensed open standards in digital library applications is now a genuine alternative to commercial or proprietary systems.
Directory of Open Access Journals (Sweden)
Wanxing Sheng
2014-01-01
Full Text Available To solve the comprehensive multiobjective optimization problem, this study proposes an improved metaheuristic searching algorithm with combination of harmony search and the fast nondominated sorting approach. This is a kind of the novel intelligent optimization algorithm for multiobjective harmony search (MOHS. The detailed description and the algorithm formulating are discussed. Taking the optimal placement and sizing issue of distributed generation (DG in distributed power system as one example, the solving procedure of the proposed method is given. Simulation result on modified IEEE 33-bus test system and comparison with NSGA-II algorithm has proved that the proposed MOHS can get promising results for engineering application.
International Nuclear Information System (INIS)
Özyön, Serdar; Aydin, Doğan
2013-01-01
Highlights: ► Prohibited operating zone economic dispatch problem has been solved by IABC-LS. ► The losses used in the solution of the problem have been computed by B-loss matrix. ► IABC-LS method has been applied to three test systems in literature. ► The values obtained by IABC and IABC-LS are better than the results in literature. - Abstract: In this study, prohibited operating zone economic power dispatch problem which considers ramp rate limit, has been solved by incremental artificial bee colony algorithm (IABC) and incremental artificial bee colony algorithm with local search (IABC-LS) methods. The transmission line losses used in the solution of the problem have been computed by B-loss matrix. IABC, IABC-LS methods have been applied to three different test systems in literature which consist of 6, 15 and 40 generators. The attained optimum solution values have been compared with the optimum results in literature and have been discussed.
Influence of an Intermediate Option on the Description-Experience Gap and Information Search
Directory of Open Access Journals (Sweden)
Neha Sharma
2018-03-01
Full Text Available Research shows that people tend to overweight small probabilities in description and underweight them in experience, thereby leading to a different pattern of choices between description and experience; a phenomenon known as the Description-Experience (DE gap. However, little is known on how the addition of an intermediate option and contextual framing influences the DE gap and people’s search strategies. This paper tests the effects of an intermediate option and contextual framing on the DE gap and people’s search strategies, where problems require search for information before a consequential choice. In the first experiment, 120 participants made choice decisions across investment problems that differed in the absence or presence of an intermediate option. Results showed that adding an intermediate option did not reduce the DE gap on the maximizing option across a majority of problems. There were a large majority of choices for the intermediate option. Furthermore, there was an increase in switching between options due to the presence of the intermediate option. In the second experiment, 160 participants made choice decisions in problems like those presented in experiment 1; however, problems lacked the investment framing. Results replicated findings from the first experiment and showed a similar DE gap on the maximizing option in a majority of problems in both the absence and presence of the intermediate option. Again, there were a large majority of choices for the intermediate option. Also, there was an increase in switching between options due to the presence of the intermediate option. Meta-analyses revealed that the absence or presence of the intermediate option created certain differences in the strength of frequency and recency processes. Also, a single natural-mean heuristic model was able to account for the experimental results across both experiments. We discuss implications of our findings to consequential decisions made after
Directory of Open Access Journals (Sweden)
Jianwen Guo
2016-01-01
Full Text Available All equipment must be maintained during its lifetime to ensure normal operation. Maintenance is one of the critical roles in the success of manufacturing enterprises. This paper proposed a preventive maintenance period optimization model (PMPOM to find an optimal preventive maintenance period. By making use of the advantages of particle swarm optimization (PSO and cuckoo search (CS algorithm, a hybrid optimization algorithm of PSO and CS is proposed to solve the PMPOM problem. The test functions show that the proposed algorithm exhibits more outstanding performance than particle swarm optimization and cuckoo search. Experiment results show that the proposed algorithm has advantages of strong optimization ability and fast convergence speed to solve the PMPOM problem.
Direct Tests on Individual Behaviour in Small Decision-Making Problems
Directory of Open Access Journals (Sweden)
Takemi Fujikawa
2007-10-01
Full Text Available This paper provides an empirical and experimental analysis of individual decision making in small decision-making problems with a series of laboratory experiments. Two experimental treatments with binary small decision-making problems are implemented: (1 the search treatment with the unknown payoff distribution to the decision makers and (2 the choice treatment with the known payoff distribution. A first observation is that in the search treatment the tendency to select best reply to the past performances, and misestimation of the payoff distribution can lead to robust deviations from expected value maximisation. A second observation is concerned with choice problems with two options with the same expected value: one option is more risky with larger payoff variability; the other option is moderate with less payoff variability. Experimental results show that it is likely that the more the decision makers choose a risky option, the higher they can achieve high points, ex post. Finally, I investigate the exploration tendency. Comparison of results between the search treatment and the choice treatment reveals that the additional information to the decision makers enhances expected value maximisation.
An Improved Harmony Search Algorithm for Power Distribution Network Planning
Directory of Open Access Journals (Sweden)
Wei Sun
2015-01-01
Full Text Available Distribution network planning because of involving many variables and constraints is a multiobjective, discrete, nonlinear, and large-scale optimization problem. Harmony search (HS algorithm is a metaheuristic algorithm inspired by the improvisation process of music players. HS algorithm has several impressive advantages, such as easy implementation, less adjustable parameters, and quick convergence. But HS algorithm still has some defects such as premature convergence and slow convergence speed. According to the defects of the standard algorithm and characteristics of distribution network planning, an improved harmony search (IHS algorithm is proposed in this paper. We set up a mathematical model of distribution network structure planning, whose optimal objective function is to get the minimum annual cost and constraint conditions are overload and radial network. IHS algorithm is applied to solve the complex optimization mathematical model. The empirical results strongly indicate that IHS algorithm can effectively provide better results for solving the distribution network planning problem compared to other optimization algorithms.
Multispecies Coevolution Particle Swarm Optimization Based on Previous Search History
Directory of Open Access Journals (Sweden)
Danping Wang
2017-01-01
Full Text Available A hybrid coevolution particle swarm optimization algorithm with dynamic multispecies strategy based on K-means clustering and nonrevisit strategy based on Binary Space Partitioning fitness tree (called MCPSO-PSH is proposed. Previous search history memorized into the Binary Space Partitioning fitness tree can effectively restrain the individuals’ revisit phenomenon. The whole population is partitioned into several subspecies and cooperative coevolution is realized by an information communication mechanism between subspecies, which can enhance the global search ability of particles and avoid premature convergence to local optimum. To demonstrate the power of the method, comparisons between the proposed algorithm and state-of-the-art algorithms are grouped into two categories: 10 basic benchmark functions (10-dimensional and 30-dimensional, 10 CEC2005 benchmark functions (30-dimensional, and a real-world problem (multilevel image segmentation problems. Experimental results show that MCPSO-PSH displays a competitive performance compared to the other swarm-based or evolutionary algorithms in terms of solution accuracy and statistical tests.
Heuristic Search for Planning with Different Forced Goal-Ordering Constraints
Directory of Open Access Journals (Sweden)
Jiangfeng Luo
2013-01-01
Full Text Available Planning with forced goal-ordering (FGO constraints has been proposed many times over the years, but there are still major difficulties in realizing these FGOs in plan generation. In certain planning domains, all the FGOs exist in the initial state. No matter which approach is adopted to achieve a subgoal, all the subgoals should be achieved in a given sequence from the initial state. Otherwise, the planning may arrive at a deadlock. For some other planning domains, there is no FGO in the initial state. However, FGO may occur during the planning process if certain subgoal is achieved by an inappropriate approach. This paper contributes to illustrate that it is the excludable constraints among the goal achievement operations (GAO of different subgoals that introduce the FGOs into the planning problem, and planning with FGO is still a challenge for the heuristic search based planners. Then, a novel multistep forward search algorithm is proposed which can solve the planning problem with different FGOs efficiently.
Hybrid Artificial Bee Colony Algorithm and Particle Swarm Search for Global Optimization
Directory of Open Access Journals (Sweden)
Wang Chun-Feng
2014-01-01
Full Text Available Artificial bee colony (ABC algorithm is one of the most recent swarm intelligence based algorithms, which has been shown to be competitive to other population-based algorithms. However, there is still an insufficiency in ABC regarding its solution search equation, which is good at exploration but poor at exploitation. To overcome this problem, we propose a novel artificial bee colony algorithm based on particle swarm search mechanism. In this algorithm, for improving the convergence speed, the initial population is generated by using good point set theory rather than random selection firstly. Secondly, in order to enhance the exploitation ability, the employed bee, onlookers, and scouts utilize the mechanism of PSO to search new candidate solutions. Finally, for further improving the searching ability, the chaotic search operator is adopted in the best solution of the current iteration. Our algorithm is tested on some well-known benchmark functions and compared with other algorithms. Results show that our algorithm has good performance.
National Research Council Canada - National Science Library
Homaifar, Abdollah; Esterline, Albert; Kimiaghalam, Bahram
2005-01-01
The Hybrid Projected Gradient-Evolutionary Search Algorithm (HPGES) algorithm uses a specially designed evolutionary-based global search strategy to efficiently create candidate solutions in the solution space...
Improved Harmony Search Algorithm with Chaos for Absolute Value Equation
Directory of Open Access Journals (Sweden)
Shouheng Tuo
2013-11-01
Full Text Available In this paper, an improved harmony search with chaos (HSCH is presented for solving NP-hard absolute value equation (AVE Ax - |x| = b, where A is an arbitrary square matrix whose singular values exceed one. The simulation results in solving some given AVE problems demonstrate that the HSCH algorithm is valid and outperforms the classical HS algorithm (CHS and HS algorithm with differential mutation operator (HSDE.
Effects of Diacritics on Web Search Engines’ Performance for Retrieval of Yoruba Documents
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Toluwase Victor Asubiaro
2014-06-01
Full Text Available This paper aims to find out the possible effect of the use or nonuse of diacritics in Yoruba search queries on the performance of major search engines, AOL, Bing, Google and Yahoo!, in retrieving documents. 30 Yoruba queries created from the most searched keywords from Nigeria on Google search logs were submitted to the search engines. The search queries were posed to the search engines without diacritics and then with diacritics. All of the search engines retrieved more sites in response to the queries without diacritics. Also, they all retrieved more precise results for queries without diacritics. The search engines also answered more queries without diacritics. There was no significant difference in the precision values of any two of the four search engines for diacritized and undiacritized queries. There was a significant difference in the effectiveness of AOL and Yahoo when diacritics were applied and when they were not applied. The findings of the study indicate that the search engines do not find a relationship between the diacritized Yoruba words and the undiacritized versions. Therefore, there is a need for search engines to add normalization steps to pre-process Yoruba queries and indexes. This study concentrates on a problem with search engines that has not been previously investigated.
International Nuclear Information System (INIS)
Tokovinin, A.A.
1986-01-01
The problem of search for star planets is discussed in a popular form. Two methods of search for planets are considered: astrometric and spectral. Both methods complement one another. An assumption is made that potential possessors of planets are in the first place yellow and red dwarfs with slow axial rotation. These stars are the most numerous representatives of Galaxy population
Directory of Open Access Journals (Sweden)
Mohammad Taghi Ameli
2012-01-01
Full Text Available Transmission Network Expansion Planning (TNEP is a basic part of power network planning that determines where, when and how many new transmission lines should be added to the network. So, the TNEP is an optimization problem in which the expansion purposes are optimized. Artificial Intelligence (AI tools such as Genetic Algorithm (GA, Simulated Annealing (SA, Tabu Search (TS and Artificial Neural Networks (ANNs are methods used for solving the TNEP problem. Today, by using the hybridization models of AI tools, we can solve the TNEP problem for large-scale systems, which shows the effectiveness of utilizing such models. In this paper, a new approach to the hybridization model of Probabilistic Neural Networks (PNNs and Harmony Search Algorithm (HSA was used to solve the TNEP problem. Finally, by considering the uncertain role of the load based on a scenario technique, this proposed model was tested on the Garver’s 6-bus network.
Directory of Open Access Journals (Sweden)
Hutton Catherine
2007-05-01
Full Text Available Abstract Background Psychological problems present a huge burden of illness in our community and GPs are the main providers of care. There is evidence that longer consultations in general practice are associated with improved quality of care; but this needs to be balanced against the fact that doctor time is a limited resource and longer consultations may lead to reduced access to health care. The aim of this research was to conduct a systematic literature review to determine whether management of psychological problems in general practice is associated with an increased consultation length and to explore whether longer consultations are associated with better health outcomes for patients with psychological problems. Methods A search was conducted on Medline (Ovid databases up to7 June 2006. The following search terms, were used: general practice or primary health care (free text or family practice (MeSH AND consultation length or duration (free text or time factors (MeSH AND depression or psychological problems or depressed (free text. A similar search was done in Web of Science, Pubmed, Google Scholar, and Cochrane Library and no other papers were found. Studies were included if they contained data comparing consultation length and management or detection of psychological problems in a general practice or primary health care setting. The studies were read and categories developed to enable systematic data extraction and synthesis. Results 29 papers met the inclusion criteria. Consultations with a recorded diagnosis of a psychological problem were reported to be longer than those with no recorded psychological diagnosis. It is not clear if this is related to the extra time or the consultation style. GPs reported that time pressure is a major barrier to treating depression. There was some evidence that increased consultation length is associated with more accurate diagnosis of psychological problems. Conclusion Further research is needed to
Texts of the New Nature: Problems of Interdisciplinary Research
Directory of Open Access Journals (Sweden)
Kazakova E.I.,
2017-02-01
Full Text Available The paper explores a new research direction unfolding at the junction of modern textual criticism and modernization challenges in education. It outlines the theoretical basis for constructing a model of the «new literacy» representative of the 21st century. The paper contains an attempt to describe the main trends in the changes of text: rejection of linearity, shrinkage of text volume, orientation to «small text structures», duplicative character of different sign systems in the content reflection, increase of interactivity, feedback forms development, emergence of «new forms of authorship» and a number of other trends. Examples are given of new literature, created in the form of comics, presentations, infographics, drawn notes. The author reveals the scope of «the texts of the new nature» through the provision of its characteristics; describes two main technologies of formation of such texts; provides experimental data that characterize the process of perception of this kind of texts; and, finally, formulates priority research issues.
Axions-motivation, limits and searches
International Nuclear Information System (INIS)
Raffelt, G G
2007-01-01
The axion solution of the strong CP problem provides a number of possible windows to physics beyond the standard model, notably in the form of searches for solar axions and for galactic axion dark matter, but in a broader context also inspires searches for axion-like particles in pure laboratory experiments. We briefly review the motivation for axions, astrophysical limits, their possible cosmological role, and current searches for axions and axion-like particles
Search-Order Independent State Caching
DEFF Research Database (Denmark)
Evangelista, Sami; Kristensen, Lars Michael
2009-01-01
State caching is a memory reduction technique used by model checkers to alleviate the state explosion problem. It has traditionally been coupled with a depth-first search to ensure termination.We propose and experimentally evaluate an extension of the state caching method for general state...... exploring algorithms that are independent of the search order (i.e., search algorithms that partition the state space into closed (visited) states, open (to visit) states and unmet states)....
Search algorithms as a framework for the optimization of drug combinations.
Directory of Open Access Journals (Sweden)
Diego Calzolari
2008-12-01
Full Text Available Combination therapies are often needed for effective clinical outcomes in the management of complex diseases, but presently they are generally based on empirical clinical experience. Here we suggest a novel application of search algorithms -- originally developed for digital communication -- modified to optimize combinations of therapeutic interventions. In biological experiments measuring the restoration of the decline with age in heart function and exercise capacity in Drosophila melanogaster, we found that search algorithms correctly identified optimal combinations of four drugs using only one-third of the tests performed in a fully factorial search. In experiments identifying combinations of three doses of up to six drugs for selective killing of human cancer cells, search algorithms resulted in a highly significant enrichment of selective combinations compared with random searches. In simulations using a network model of cell death, we found that the search algorithms identified the optimal combinations of 6-9 interventions in 80-90% of tests, compared with 15-30% for an equivalent random search. These findings suggest that modified search algorithms from information theory have the potential to enhance the discovery of novel therapeutic drug combinations. This report also helps to frame a biomedical problem that will benefit from an interdisciplinary effort and suggests a general strategy for its solution.
Deb, Kalyanmoy; Sinha, Ankur
2010-01-01
Bilevel optimization problems involve two optimization tasks (upper and lower level), in which every feasible upper level solution must correspond to an optimal solution to a lower level optimization problem. These problems commonly appear in many practical problem solving tasks including optimal control, process optimization, game-playing strategy developments, transportation problems, and others. However, they are commonly converted into a single level optimization problem by using an approximate solution procedure to replace the lower level optimization task. Although there exist a number of theoretical, numerical, and evolutionary optimization studies involving single-objective bilevel programming problems, not many studies look at the context of multiple conflicting objectives in each level of a bilevel programming problem. In this paper, we address certain intricate issues related to solving multi-objective bilevel programming problems, present challenging test problems, and propose a viable and hybrid evolutionary-cum-local-search based algorithm as a solution methodology. The hybrid approach performs better than a number of existing methodologies and scales well up to 40-variable difficult test problems used in this study. The population sizing and termination criteria are made self-adaptive, so that no additional parameters need to be supplied by the user. The study indicates a clear niche of evolutionary algorithms in solving such difficult problems of practical importance compared to their usual solution by a computationally expensive nested procedure. The study opens up many issues related to multi-objective bilevel programming and hopefully this study will motivate EMO and other researchers to pay more attention to this important and difficult problem solving activity.
A hybrid genetic algorithm for the distributed permutation flowshop scheduling problem
Directory of Open Access Journals (Sweden)
Jian Gao
2011-08-01
Full Text Available Distributed Permutation Flowshop Scheduling Problem (DPFSP is a newly proposed scheduling problem, which is a generalization of classical permutation flow shop scheduling problem. The DPFSP is NP-hard in general. It is in the early stages of studies on algorithms for solving this problem. In this paper, we propose a GA-based algorithm, denoted by GA_LS, for solving this problem with objective to minimize the maximum completion time. In the proposed GA_LS, crossover and mutation operators are designed to make it suitable for the representation of DPFSP solutions, where the set of partial job sequences is employed. Furthermore, GA_LS utilizes an efficient local search method to explore neighboring solutions. The local search method uses three proposed rules that move jobs within a factory or between two factories. Intensive experiments on the benchmark instances, extended from Taillard instances, are carried out. The results indicate that the proposed hybrid genetic algorithm can obtain better solutions than all the existing algorithms for the DPFSP, since it obtains better relative percentage deviation and differences of the results are also statistically significant. It is also seen that best-known solutions for most instances are updated by our algorithm. Moreover, we also show the efficiency of the GA_LS by comparing with similar genetic algorithms with the existing local search methods.
Understanding search trees via statistical physics
Indian Academy of Sciences (India)
ary search tree model (where stands for the number of branches of the search tree), an important problem for data storage in computer science, using a variety of statistical physics techniques that allow us to obtain exact asymptotic results.
Ant colony optimization techniques for the hamiltonian p-median problem
Directory of Open Access Journals (Sweden)
M. Zohrehbandian
2010-12-01
Full Text Available Location-Routing problems involve locating a number of facilitiesamong candidate sites and establishing delivery routes to a set of users in such a way that the total system cost is minimized. A special case of these problems is Hamiltonian p-Median problem (HpMP. This research applies the metaheuristic method of ant colony optimization (ACO to solve the HpMP. Modifications are made to the ACO algorithm used to solve the traditional vehicle routing problem (VRP in order to allow the search of the optimal solution of the HpMP. Regarding this metaheuristic algorithm a computational experiment is reported as well.
Multipass Target Search in Natural Environments.
Kuhlman, Michael J; Otte, Michael W; Sofge, Donald; Gupta, Satyandra K
2017-11-02
Consider a disaster scenario where search and rescue workers must search difficult to access buildings during an earthquake or flood. Often, finding survivors a few hours sooner results in a dramatic increase in saved lives, suggesting the use of drones for expedient rescue operations. Entropy can be used to quantify the generation and resolution of uncertainty. When searching for targets, maximizing mutual information of future sensor observations will minimize expected target location uncertainty by minimizing the entropy of the future estimate. Motion planning for multi-target autonomous search requires planning over an area with an imperfect sensor and may require multiple passes, which is hindered by the submodularity property of mutual information. Further, mission duration constraints must be handled accordingly, requiring consideration of the vehicle's dynamics to generate feasible trajectories and must plan trajectories spanning the entire mission duration, something which most information gathering algorithms are incapable of doing. If unanticipated changes occur in an uncertain environment, new plans must be generated quickly. In addition, planning multipass trajectories requires evaluating path dependent rewards, requiring planning in the space of all previously selected actions, compounding the problem. We present an anytime algorithm for autonomous multipass target search in natural environments. The algorithm is capable of generating long duration dynamically feasible multipass coverage plans that maximize mutual information using a variety of techniques such as ϵ -admissible heuristics to speed up the search. To the authors' knowledge this is the first attempt at efficiently solving multipass target search problems of such long duration. The proposed algorithm is based on best first branch and bound and is benchmarked against state of the art algorithms adapted to the problem in natural Simplex environments, gathering the most information in the
Particle Swarm Optimization for Structural Design Problems
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Hamit SARUHAN
2010-02-01
Full Text Available The aim of this paper is to employ the Particle Swarm Optimization (PSO technique to a mechanical engineering design problem which is minimizing the volume of a cantilevered beam subject to bending strength constraints. Mechanical engineering design problems are complex activities which are computing capability are more and more required. The most of these problems are solved by conventional mathematical programming techniques that require gradient information. These techniques have several drawbacks from which the main one is becoming trapped in local optima. As an alternative to gradient-based techniques, the PSO does not require the evaluation of gradients of the objective function. The PSO algorithm employs the generation of guided random positions when they search for the global optimum point. The PSO which is a nature inspired heuristics search technique imitates the social behavior of bird flocking. The results obtained by the PSO are compared with Mathematical Programming (MP. It is demonstrated that the PSO performed and obtained better convergence reliability on the global optimum point than the MP. Using the MP, the volume of 2961000 mm3 was obtained while the beam volume of 2945345 mm3 was obtained by the PSO.
Towards improving searches for optimal phylogenies.
Ford, Eric; St John, Katherine; Wheeler, Ward C
2015-01-01
Finding the optimal evolutionary history for a set of taxa is a challenging computational problem, even when restricting possible solutions to be "tree-like" and focusing on the maximum-parsimony optimality criterion. This has led to much work on using heuristic tree searches to find approximate solutions. We present an approach for finding exact optimal solutions that employs and complements the current heuristic methods for finding optimal trees. Given a set of taxa and a set of aligned sequences of characters, there may be subsets of characters that are compatible, and for each such subset there is an associated (possibly partially resolved) phylogeny with edges corresponding to each character state change. These perfect phylogenies serve as anchor trees for our constrained search space. We show that, for sequences with compatible sites, the parsimony score of any tree [Formula: see text] is at least the parsimony score of the anchor trees plus the number of inferred changes between [Formula: see text] and the anchor trees. As the maximum-parsimony optimality score is additive, the sum of the lower bounds on compatible character partitions provides a lower bound on the complete alignment of characters. This yields a region in the space of trees within which the best tree is guaranteed to be found; limiting the search for the optimal tree to this region can significantly reduce the number of trees that must be examined in a search of the space of trees. We analyze this method empirically using four different biological data sets as well as surveying 400 data sets from the TreeBASE repository, demonstrating the effectiveness of our technique in reducing the number of steps in exact heuristic searches for trees under the maximum-parsimony optimality criterion. © The Author(s) 2014. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Hybrid Genetic Algorithm with Multiparents Crossover for Job Shop Scheduling Problems
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Noor Hasnah Moin
2015-01-01
Full Text Available The job shop scheduling problem (JSSP is one of the well-known hard combinatorial scheduling problems. This paper proposes a hybrid genetic algorithm with multiparents crossover for JSSP. The multiparents crossover operator known as extended precedence preservative crossover (EPPX is able to recombine more than two parents to generate a single new offspring distinguished from common crossover operators that recombine only two parents. This algorithm also embeds a schedule generation procedure to generate full-active schedule that satisfies precedence constraints in order to reduce the search space. Once a schedule is obtained, a neighborhood search is applied to exploit the search space for better solutions and to enhance the GA. This hybrid genetic algorithm is simulated on a set of benchmarks from the literatures and the results are compared with other approaches to ensure the sustainability of this algorithm in solving JSSP. The results suggest that the implementation of multiparents crossover produces competitive results.
RNA motif search with data-driven element ordering.
Rampášek, Ladislav; Jimenez, Randi M; Lupták, Andrej; Vinař, Tomáš; Brejová, Broňa
2016-05-18
In this paper, we study the problem of RNA motif search in long genomic sequences. This approach uses a combination of sequence and structure constraints to uncover new distant homologs of known functional RNAs. The problem is NP-hard and is traditionally solved by backtracking algorithms. We have designed a new algorithm for RNA motif search and implemented a new motif search tool RNArobo. The tool enhances the RNAbob descriptor language, allowing insertions in helices, which enables better characterization of ribozymes and aptamers. A typical RNA motif consists of multiple elements and the running time of the algorithm is highly dependent on their ordering. By approaching the element ordering problem in a principled way, we demonstrate more than 100-fold speedup of the search for complex motifs compared to previously published tools. We have developed a new method for RNA motif search that allows for a significant speedup of the search of complex motifs that include pseudoknots. Such speed improvements are crucial at a time when the rate of DNA sequencing outpaces growth in computing. RNArobo is available at http://compbio.fmph.uniba.sk/rnarobo .
Optimal Results and Numerical Simulations for Flow Shop Scheduling Problems
Directory of Open Access Journals (Sweden)
Tao Ren
2012-01-01
Full Text Available This paper considers the m-machine flow shop problem with two objectives: makespan with release dates and total quadratic completion time, respectively. For Fm|rj|Cmax, we prove the asymptotic optimality for any dense scheduling when the problem scale is large enough. For Fm‖ΣCj2, improvement strategy with local search is presented to promote the performance of the classical SPT heuristic. At the end of the paper, simulations show the effectiveness of the improvement strategy.
Directory of Open Access Journals (Sweden)
Надежда Алексеевна Дудик
2014-12-01
Full Text Available The most fundamental problem involved in the theory and practice of translation from one language into another consists in achieving adequacy between the source language (SL and the target language (TL. Adequacy can be reached by means of employing the communication strategy, i.e. by discussing the dialogue nature of the text in particular; by analyzing realia in translation in terms of the text as a whole, rather than as isolated units in the system of language; and by looking at how the semantic category of intensity influences the translatability of the Russian fiction text into English. The research has shown that the aspects examined are typical of Russian-English translation in general rather than of a single text.
Solving Dynamic Traveling Salesman Problem Using Dynamic Gaussian Process Regression
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Stephen M. Akandwanaho
2014-01-01
Full Text Available This paper solves the dynamic traveling salesman problem (DTSP using dynamic Gaussian Process Regression (DGPR method. The problem of varying correlation tour is alleviated by the nonstationary covariance function interleaved with DGPR to generate a predictive distribution for DTSP tour. This approach is conjoined with Nearest Neighbor (NN method and the iterated local search to track dynamic optima. Experimental results were obtained on DTSP instances. The comparisons were performed with Genetic Algorithm and Simulated Annealing. The proposed approach demonstrates superiority in finding good traveling salesman problem (TSP tour and less computational time in nonstationary conditions.
Directory of Open Access Journals (Sweden)
John E. Candelo-Becerra
2015-07-01
Full Text Available Electric power losses have a significant impact on the total costs of distribution networks. The use of renewable energy sources is a major alternative to improve power losses and costs, although other important issues are also enhanced such as voltage magnitudes and network congestion. However, determining the best location and size of renewable energy generators can be sometimes a challenging task due to a large number of possible combinations in the search space. Furthermore, the multiobjective functions increase the complexity of the problem and metaheuristics are preferred to find solutions in a relatively short time. This paper evaluates the performance of the cuckoo search (CS, harmony search (HS, and bat-inspired (BA algorithms for the location and size of renewable distributed generation (RDG in radial distribution networks using a multiobjective function defined as minimizing the energy losses and the RDG costs. The metaheuristic algorithms were programmed in Matlab and tested using the 33-node radial distribution network. The three algorithms obtained similar results for the two objectives evaluated, finding points close to the best solutions in the Pareto front. Comparisons showed that the CS obtained the minimum results for most points evaluated, but the BA and the HS were close to the best solution.
User Intent in Online Video Search
Kofler, C.
2015-01-01
Over the recent years, user expectations of the ability of video search engines have significantly risen. Users expect video search engines to be useful as an instrument that facilitates communication, education, entertainment and problem solving and, in relation to this, to satisfy diverse
Cuckoo Search with flight of Levy applied to the problem of reload of fuels in nuclear reactors
International Nuclear Information System (INIS)
Silva, Patrick V.; Nast, Fernando N.; Schirru, Roberto; Meneses, Anderson A.M.; Coordenacao de Pos-Graduacao e Pesquisa de Engenharia
2017-01-01
Intra-Nuclear Fuel Management Optimization is a complex combinatorial problem of the NP-difficult type, associated with the refueling process of a nuclear reactor, which aims to extend the cycle of operation by determining loading patterns, obeying safety margins. In addition to the combinatorial problem, we have the aspect of calculations of reactor physics, which increases the difficult of OGCIN. Methods that are proving effective when applied to OGCIN are the algorithms belonging to the swarm intelligence paradigm. A new member of this paradigm is Cuckoo Search (CS), which has shown results promising when applied to optimization issues. The CS is based on the litter parasitism of some cuckoo species combined with the Levy flight behavior of some birds. In the present work we present the results of the application of CS to OGCIN, and compare them to the results obtained by the application of ABC
SOLVING ENGINEERING OPTIMIZATION PROBLEMS WITH THE SWARM INTELLIGENCE METHODS
Directory of Open Access Journals (Sweden)
V. Panteleev Andrei
2017-01-01
Full Text Available An important stage in problem solving process for aerospace and aerostructures designing is calculating their main charac- teristics optimization. The results of the four constrained optimization problems related to the design of various technical systems: such as determining the best parameters of welded beams, pressure vessel, gear, spring are presented. The purpose of each task is to minimize the cost and weight of the construction. The object functions in optimization practical problem are nonlinear functions with a lot of variables and a complex layer surface indentations. That is why using classical approach for extremum seeking is not efficient. Here comes the necessity of using such methods of optimization that allow to find a near optimal solution in acceptable amount of time with the minimum waste of computer power. Such methods include the methods of Swarm Intelligence: spiral dy- namics algorithm, stochastic diffusion search, hybrid seeker optimization algorithm. The Swarm Intelligence methods are designed in such a way that a swarm consisting of agents carries out the search for extremum. In search for the point of extremum, the parti- cles exchange information and consider their experience as well as the experience of population leader and the neighbors in some area. To solve the listed problems there has been designed a program complex, which efficiency is illustrated by the solutions of four applied problems. Each of the considered applied optimization problems is solved with all the three chosen methods. The ob- tained numerical results can be compared with the ones found in a swarm with a particle method. The author gives recommenda- tions on how to choose methods parameters and penalty function value, which consider inequality constraints.
McGreevy, Michael W.; Connors, Mary M. (Technical Monitor)
2001-01-01
To support Search Requests and Quick Responses at the Aviation Safety Reporting System (ASRS), four new QUORUM methods have been developed: keyword search, phrase search, phrase generation, and phrase discovery. These methods build upon the core QUORUM methods of text analysis, modeling, and relevance-ranking. QUORUM keyword search retrieves ASRS incident narratives that contain one or more user-specified keywords in typical or selected contexts, and ranks the narratives on their relevance to the keywords in context. QUORUM phrase search retrieves narratives that contain one or more user-specified phrases, and ranks the narratives on their relevance to the phrases. QUORUM phrase generation produces a list of phrases from the ASRS database that contain a user-specified word or phrase. QUORUM phrase discovery finds phrases that are related to topics of interest. Phrase generation and phrase discovery are particularly useful for finding query phrases for input to QUORUM phrase search. The presentation of the new QUORUM methods includes: a brief review of the underlying core QUORUM methods; an overview of the new methods; numerous, concrete examples of ASRS database searches using the new methods; discussion of related methods; and, in the appendices, detailed descriptions of the new methods.
SWIFT-Review: a text-mining workbench for systematic review.
Howard, Brian E; Phillips, Jason; Miller, Kyle; Tandon, Arpit; Mav, Deepak; Shah, Mihir R; Holmgren, Stephanie; Pelch, Katherine E; Walker, Vickie; Rooney, Andrew A; Macleod, Malcolm; Shah, Ruchir R; Thayer, Kristina
2016-05-23
There is growing interest in using machine learning approaches to priority rank studies and reduce human burden in screening literature when conducting systematic reviews. In addition, identifying addressable questions during the problem formulation phase of systematic review can be challenging, especially for topics having a large literature base. Here, we assess the performance of the SWIFT-Review priority ranking algorithm for identifying studies relevant to a given research question. We also explore the use of SWIFT-Review during problem formulation to identify, categorize, and visualize research areas that are data rich/data poor within a large literature corpus. Twenty case studies, including 15 public data sets, representing a range of complexity and size, were used to assess the priority ranking performance of SWIFT-Review. For each study, seed sets of manually annotated included and excluded titles and abstracts were used for machine training. The remaining references were then ranked for relevance using an algorithm that considers term frequency and latent Dirichlet allocation (LDA) topic modeling. This ranking was evaluated with respect to (1) the number of studies screened in order to identify 95 % of known relevant studies and (2) the "Work Saved over Sampling" (WSS) performance metric. To assess SWIFT-Review for use in problem formulation, PubMed literature search results for 171 chemicals implicated as EDCs were uploaded into SWIFT-Review (264,588 studies) and categorized based on evidence stream and health outcome. Patterns of search results were surveyed and visualized using a variety of interactive graphics. Compared with the reported performance of other tools using the same datasets, the SWIFT-Review ranking procedure obtained the highest scores on 11 out of 15 of the public datasets. Overall, these results suggest that using machine learning to triage documents for screening has the potential to save, on average, more than 50 % of the screening
The search for an alerted moving target; 2005BU2-OA
Vermeulen, J.F.J.; Brink, M. van den
2005-01-01
We investigate a two-sided, multi-stage search problem where a continuous search effort is made by one or more search units to detect a moving target in a continuous target space, under noisy detection conditions. A specific example of this problem is hunting for an enemy submarine by naval forces.
Rohrig, Rainer; The ATLAS collaboration
2017-01-01
The existence of Dark Matter is inferred from several astrophysical and cosmological observations. Several extensions of the Standard Model accommodating Dark Matter constraints predict associated production of Dark Matter particles with the Standard Model Higgs boson. Such models are searched for in final states with large missing transverse momentum and a Higgs boson decaying to a pair of $b$-quarks with the ATLAS detector using 36.1~fb$^{-1}$ of $pp$ collisions at a center-of-mass energy of 13~TeV at the LHC. An optimized selection together with an improved Higgs boson identification in boosted topologies leads to a significant improvement in sensitivity compared to previous searches. The observed data are in good agreement with the Standard Model predictions. Thus, limits are placed on the production cross-section of Dark Matter particles with a Higgs boson for a simplified model with two Higgs doublets and a heavy vector mediator. In addition, stringent model-independent limits are placed on the producti...
Measurement Axis Searching Model for Terrestrial Laser Scans Registration
Directory of Open Access Journals (Sweden)
Shaoxing Hu
2016-01-01
Full Text Available Nowadays, terrestrial Lidar scans can cover rather a large area; the point densities are strongly varied because of the line-of-sight measurement principle in potential overlaps with scans taken from different viewpoints. Most of the traditional methods focus on registration algorithm and ignore searching model. Sometimes the traditional methods are directly used to align two point clouds; a large critically unsolved problem of the large biases will be created in areas distant from the overlaps while the local overlaps are often aligned well. So a novel measurement axis searching model (MASM has been proposed in this paper. The method includes four steps: (1 the principal axis fitting, (2 the measurement axis generation, (3 low-high-precision search, and (4 result generation. The principal axis gives an orientation to the point cloud; the search scope is limited by the measurement axis. The point cloud orientation can be adjusted gradually until the achievement of the global optimum using low- and high-precision search. We perform some experiments with simulated point clouds and real terrestrial laser scans. The results of simulated point clouds have shown the processing steps of our method, and the results of real terrestrial laser scans have shown the sensitivity of the approach with respect to the indoor and outdoor scenes.
Directory of Open Access Journals (Sweden)
Hao Yin
2014-01-01
Full Text Available For SLA-aware service composition problem (SSC, an optimization model for this algorithm is built, and a hybrid multiobjective discrete particle swarm optimization algorithm (HMDPSO is also proposed in this paper. According to the characteristic of this problem, a particle updating strategy is designed by introducing crossover operator. In order to restrain particle swarm’s premature convergence and increase its global search capacity, the swarm diversity indicator is introduced and a particle mutation strategy is proposed to increase the swarm diversity. To accelerate the process of obtaining the feasible particle position, a local search strategy based on constraint domination is proposed and incorporated into the proposed algorithm. At last, some parameters in the algorithm HMDPSO are analyzed and set with relative proper values, and then the algorithm HMDPSO and the algorithm HMDPSO+ incorporated by local search strategy are compared with the recently proposed related algorithms on different scale cases. The results show that algorithm HMDPSO+ can solve the SSC problem more effectively.
New generation of the multimedia search engines
Mijes Cruz, Mario Humberto; Soto Aldaco, Andrea; Maldonado Cano, Luis Alejandro; López Rodríguez, Mario; Rodríguez Vázqueza, Manuel Antonio; Amaya Reyes, Laura Mariel; Cano Martínez, Elizabeth; Pérez Rosas, Osvaldo Gerardo; Rodríguez Espejo, Luis; Flores Secundino, Jesús Abimelek; Rivera Martínez, José Luis; García Vázquez, Mireya Saraí; Zamudio Fuentes, Luis Miguel; Sánchez Valenzuela, Juan Carlos; Montoya Obeso, Abraham; Ramírez Acosta, Alejandro Álvaro
2016-09-01
Current search engines are based upon search methods that involve the combination of words (text-based search); which has been efficient until now. However, the Internet's growing demand indicates that there's more diversity on it with each passing day. Text-based searches are becoming limited, as most of the information on the Internet can be found in different types of content denominated multimedia content (images, audio files, video files). Indeed, what needs to be improved in current search engines is: search content, and precision; as well as an accurate display of expected search results by the user. Any search can be more precise if it uses more text parameters, but it doesn't help improve the content or speed of the search itself. One solution is to improve them through the characterization of the content for the search in multimedia files. In this article, an analysis of the new generation multimedia search engines is presented, focusing the needs according to new technologies. Multimedia content has become a central part of the flow of information in our daily life. This reflects the necessity of having multimedia search engines, as well as knowing the real tasks that it must comply. Through this analysis, it is shown that there are not many search engines that can perform content searches. The area of research of multimedia search engines of new generation is a multidisciplinary area that's in constant growth, generating tools that satisfy the different needs of new generation systems.
An Effective Framework For Economic Dispatch Using Modified Harmony Search Algorithm
Directory of Open Access Journals (Sweden)
Advik Kumar
2017-09-01
Full Text Available The effects of ever-increasing wind power generation for solving the economic dispatch ED problem have led to high penetration of renewable energy source in new power systems. Continuing search for better utilizing of wind turbine associated with thermal sources to find the optimal allocation of output power is necessary in which pro-vide more reliability and efficiency. Dynamic nature of wind energy has imposed uncertainties characteristics in the poser systems. To deal with this problem an effective probabilistic method to investigate all unpredictability would be a good idea to make more realistic analysis. This paper presents a heuristics optimization method based on harmony search HS algorithm to solve non-convex ED problems while uncertainties effects caused by wind turbines are considered. To involve a realistic analysis as a more practical investigation the proposed probabilistic ED PED approach includes prohibited operating zone POZ system spinning reserve ramp rate limits variety of fuel is considered in this studies. Point Estimate Method PEM as a proposed PED model the uncertainties of wind speed for wind turbines to present better realization to the problem. Optimal solution are presented for vari-ous test system and these solutions demonstrate the benefits of our approach in terms of cost over existing ED techniques.
Ershad Sarabi, Roghayeh; Sadoughi, Farahnaz; Jamshidi Orak, Roohangiz; Bahaadinbeigy, Kambiz
2016-05-01
Medication non-adherence is a commonly observed problem in the self-administration of treatment, regardless of the disease type. Text messaging reminders, as electronic reminders, provide an opportunity to improve medication adherence. In this study, we aimed to provide evidence addressing the question of whether text message reminders were effective in improving patients' adherence to medication. We carried out a systematic literature search, using the five electronic bibliographic databases: PubMed, Embase, PsycINFO, CINAHL, and the Cochrane central register of controlled trials. Studies were included on the basis of whether they examined the benefits and effects of short-message service (SMS) interventions on medication adherence. The results of this systematic review indicated that text messaging interventions have improved patients' medication adherence rate (85%, 29.34). Included in the review, those who had problems with adherence, or those whom text messaging was most helpful had HIV, asthma, diabetes, schizophrenia and heart disease (73.5%). The period of intervention varied from 1 week to 14 months. The most common study design was randomized controlled trials (RCTs) (66%) carried out in the developed countries. This study demonstrated the potential of mobile phone text messaging for medication non-adherence problem solving.
Job shop scheduling by local search
Vaessens, R.J.M.; Aarts, E.H.L.; Lenstra, J.K.
1994-01-01
We survey solution methods for the job shop scheduling problem with an emphasis on local search. We discuss both cleterministic and randomized local search methods as well as the applied neighborhoods. We compare the computational performance of the various methods in terms of their effectiveness
Solving Environmental Problems
DEFF Research Database (Denmark)
Ørding Olsen, Anders; Sofka, Wolfgang; Grimpe, Christoph
2017-01-01
for Research and Technological Development (FP7), our results indicate that the problem-solving potential of a search strategy increases with the diversity of existing knowledge of the partners in a consortium and with the experience of the partners involved. Moreover, we identify a substantial negative effect...... dispersed. Hence, firms need to collaborate. We shed new light on collaborative search strategies led by firms in general and for solving environmental problems in particular. Both topics are largely absent in the extant open innovation literature. Using data from the European Seventh Framework Program...
Directory of Open Access Journals (Sweden)
S. Selvi
2015-07-01
Full Text Available Grid computing solves high performance and high-throughput computing problems through sharing resources ranging from personal computers to super computers distributed around the world. As the grid environments facilitate distributed computation, the scheduling of grid jobs has become an important issue. In this paper, an investigation on implementing Multiobjective Variable Neighborhood Search (MVNS algorithm for scheduling independent jobs on computational grid is carried out. The performance of the proposed algorithm has been evaluated with Min–Min algorithm, Simulated Annealing (SA and Greedy Randomized Adaptive Search Procedure (GRASP algorithm. Simulation results show that MVNS algorithm generally performs better than other metaheuristics methods.
Searching for Orphan radiation sources
International Nuclear Information System (INIS)
Bystrov, Evgenij; Antonau, Uladzimir; Gurinovich, Uladzimir; Kazhamiakin, Valery; Petrov, Vitaly; Shulhovich, Heorhi; Tischenko, Siarhei
2008-01-01
Full text: The problem of orphan sources cannot be left unaddressed due high probability of accidental exposure and use of sources for terrorism. Search of objects of this kind is complex particularly when search territory is large. This requires devices capable of detecting sources, identifying their radionuclide composition, and correlating scan results to geographical coordinates and displaying results on a map. Spectral radiation scanner AT6101C can fulfill the objective of search for gamma and neutron radiation sources, radionuclide composition identification, correlation results to geographical coordinates and displaying results on a map. The scanner consists of gamma radiation scintillation detection unit based on NaI(Tl) crystal, neutron detection unit based on two He 3 counters, GPS receiver and portable ruggedized computer. Built-in and application software automates entire scan process, saving all results to memory for further analysis with visual representation of results as spectral information diagrams, count rate profile and gamma radiation dose rates on a geographical map. The scanner informs operator with voice messages on detection of radiation sources, identification result and other events. Scanner detection units and accessories are packed in a backpack. Weighing 7 kg, the scanner is human portable and can be used for scan inside cars. The scanner can also be used for radiation mapping and inspections. (author)
Problem-based learning for technical students on the base TRIZ (theory of inventive problem solving
Directory of Open Access Journals (Sweden)
Babenko Oksana
2016-01-01
Full Text Available The basis of modern educational technology in teaching is problem-based learning through the use of educational technologies Powerful Thinking - Theory of Inventive Problem Solving (TRIZ, including a systematic approach to the complex organization of independent work of search and research character. Developed by systemic administration of the physical features workshops on the basis TRIZ in the cycle of the natural sciences with the implementation of all aspects of the educational activities - substantive, procedural and motivational. A new model of the physical design of the workshop and its form of organization, which is based on problem-based learning with the use of TRIZ Interactive form of organization of the workshop allows you to get high-quality substantive and personality of the students who have a significant role in the formation of professional competencies and affect the quality of produce practice-oriented specialists.
Energy Technology Data Exchange (ETDEWEB)
Hollaar, L A
1983-10-01
The Utah Text Retrieval project seeks well-engineered solutions to the implementation of large, inexpensive, rapid text information retrieval systems. The project has three major components. Perhaps the best known is the work on the specialized processors, particularly search engines, necessary to achieve the desired performance and cost. The other two concern the user interface to the system and the system's internal structure. The work on user interface development is not only concentrating on the syntax and semantics of the query language, but also on the overall environment the system presents to the user. Environmental enhancements include convenient ways to browse through retrieved documents, access to other information retrieval systems through gateways supporting a common command interface, and interfaces to word processing systems. The system's internal structure is based on a high-level data communications protocol linking the user interface, index processor, search processor, and other system modules. This allows them to be easily distributed in a multi- or specialized-processor configuration. It also allows new modules, such as a knowledge-based query reformulator, to be added. 15 references.
CONFORMATIONAL SEARCH BY POTENTIAL-ENERGY ANNEALING - ALGORITHM AND APPLICATION TO CYCLOSPORINE-A
VANSCHAIK, RC; VANGUNSTEREN, WF; BERENDSEN, HJC
A major problem in modelling (biological) macromolecules is the search for low-energy conformations. The complexity of a conformational search problem increases exponentially with the number of degrees of freedom which means that a systematic search can only be performed for very small structures.
BOSS: context-enhanced search for biomedical objects
Directory of Open Access Journals (Sweden)
Choi Jaehoon
2012-04-01
Full Text Available Abstract Background There exist many academic search solutions and most of them can be put on either ends of spectrum: general-purpose search and domain-specific "deep" search systems. The general-purpose search systems, such as PubMed, offer flexible query interface, but churn out a list of matching documents that users have to go through the results in order to find the answers to their queries. On the other hand, the "deep" search systems, such as PPI Finder and iHOP, return the precompiled results in a structured way. Their results, however, are often found only within some predefined contexts. In order to alleviate these problems, we introduce a new search engine, BOSS, Biomedical Object Search System. Methods Unlike the conventional search systems, BOSS indexes segments, rather than documents. A segment refers to a Maximal Coherent Semantic Unit (MCSU such as phrase, clause or sentence that is semantically coherent in the given context (e.g., biomedical objects or their relations. For a user query, BOSS finds all matching segments, identifies the objects appearing in those segments, and aggregates the segments for each object. Finally, it returns the ranked list of the objects along with their matching segments. Results The working prototype of BOSS is available at http://boss.korea.ac.kr. The current version of BOSS has indexed abstracts of more than 20 million articles published during last 16 years from 1996 to 2011 across all science disciplines. Conclusion BOSS fills the gap between either ends of the spectrum by allowing users to pose context-free queries and by returning a structured set of results. Furthermore, BOSS exhibits the characteristic of good scalability, just as with conventional document search engines, because it is designed to use a standard document-indexing model with minimal modifications. Considering the features, BOSS notches up the technological level of traditional solutions for search on biomedical information.
Aaboud, M; Aad, G; Abbott, B; Abdallah, J; Abdinov, O; Abeloos, B; Aben, R; AbouZeid, O S; Abraham, N L; Abramowicz, H; Abreu, H; Abreu, R; Abulaiti, Y; Acharya, B S; Adachi, S; Adamczyk, L; Adams, D L; Adelman, J; Adomeit, S; Adye, T; Affolder, A A; Agatonovic-Jovin, T; Agricola, J; Aguilar-Saavedra, J A; Ahlen, S P; Ahmadov, F; Aielli, G; Akerstedt, H; Åkesson, T P A; Akimov, A V; Alberghi, G L; Albert, J; Albrand, S; Verzini, M J Alconada; Aleksa, M; Aleksandrov, I N; Alexa, C; Alexander, G; Alexopoulos, T; Alhroob, M; Ali, B; Aliev, M; Alimonti, G; Alison, J; Alkire, S P; Allbrooke, B M M; Allen, B W; Allport, P P; Aloisio, A; Alonso, A; Alonso, F; Alpigiani, C; Alshehri, A A; Alstaty, M; Gonzalez, B Alvarez; Piqueras, D Álvarez; Alviggi, M G; Amadio, B T; Amako, K; Coutinho, Y Amaral; Amelung, C; Amidei, D; Santos, S P Amor Dos; Amorim, A; Amoroso, S; Amundsen, G; Anastopoulos, C; Ancu, L S; Andari, N; Andeen, T; Anders, C F; Anders, G; Anders, J K; Anderson, K J; Andreazza, A; Andrei, V; Angelidakis, S; Angelozzi, I; Anger, P; Angerami, A; Anghinolfi, F; Anisenkov, A V; Anjos, N; Annovi, A; Antel, C; Antonelli, M; Antonov, A; Anulli, F; Aoki, M; Bella, L Aperio; Arabidze, G; Arai, Y; Araque, J P; Arce, A T H; Arduh, F A; Arguin, J-F; Argyropoulos, S; Arik, M; Armbruster, A J; Armitage, L J; Arnaez, O; Arnold, H; Arratia, M; Arslan, O; Artamonov, A; Artoni, G; Artz, S; Asai, S; Asbah, N; Ashkenazi, A; Åsman, B; Asquith, L; Assamagan, K; Astalos, R; Atkinson, M; Atlay, N B; Augsten, K; Avolio, G; Axen, B; Ayoub, M K; Azuelos, G; Baak, M A; Baas, A E; Baca, M J; Bachacou, H; Bachas, K; Backes, M; Backhaus, M; Bagiacchi, P; Bagnaia, P; Bai, Y; Baines, J T; Baker, O K; Baldin, E M; Balek, P; Balestri, T; Balli, F; Balunas, W K; Banas, E; Banerjee, Sw; Bannoura, A A E; Barak, L; Barberio, E L; Barberis, D; Barbero, M; Barillari, T; Barisits, M-S; Barklow, T; Barlow, N; Barnes, S L; Barnett, B M; Barnett, R M; Barnovska-Blenessy, Z; Baroncelli, A; Barone, G; Barr, A J; Navarro, L Barranco; Barreiro, F; da Costa, J Barreiro Guimarães; Bartoldus, R; Barton, A E; Bartos, P; Basalaev, A; Bassalat, A; Bates, R L; Batista, S J; Batley, J R; Battaglia, M; Bauce, M; Bauer, F; Bawa, H S; Beacham, J B; Beattie, M D; Beau, T; Beauchemin, P H; Bechtle, P; Beck, H P; Becker, K; Becker, M; Beckingham, M; Becot, C; Beddall, A J; Beddall, A; Bednyakov, V A; Bedognetti, M; Bee, C P; Beemster, L J; Beermann, T A; Begel, M; Behr, J K; Belanger-Champagne, C; Bell, A S; Bella, G; Bellagamba, L; Bellerive, A; Bellomo, M; Belotskiy, K; Beltramello, O; Belyaev, N L; Benary, O; Benchekroun, D; Bender, M; Bendtz, K; Benekos, N; Benhammou, Y; Noccioli, E Benhar; Benitez, J; Benjamin, D P; Bensinger, J R; Bentvelsen, S; Beresford, L; Beretta, M; Berge, D; Kuutmann, E Bergeaas; Berger, N; Beringer, J; Berlendis, S; Bernard, N R; Bernius, C; Bernlochner, F U; Berry, T; Berta, P; Bertella, C; Bertoli, G; Bertolucci, F; Bertram, I A; Bertsche, C; Bertsche, D; Besjes, G J; Bylund, O Bessidskaia; Bessner, M; 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Winston, O J; Winter, B T; Wittgen, M; Wittkowski, J; Wolf, T M H; Wolter, M W; Wolters, H; Worm, S D; Wosiek, B K; Wotschack, J; Woudstra, M J; Wozniak, K W; Wu, M; Wu, M; Wu, S L; Wu, X; Wu, Y; Wyatt, T R; Wynne, B M; Xella, S; Xu, D; Xu, L; Yabsley, B; Yacoob, S; Yamaguchi, D; Yamaguchi, Y; Yamamoto, A; Yamamoto, S; Yamanaka, T; Yamauchi, K; Yamazaki, Y; Yan, Z; Yang, H; Yang, H; Yang, Y; Yang, Z; Yao, W-M; Yap, Y C; Yasu, Y; Yatsenko, E; Wong, K H Yau; Ye, J; Ye, S; Yeletskikh, I; Yen, A L; Yildirim, E; Yorita, K; Yoshida, R; Yoshihara, K; Young, C; Young, C J S; Youssef, S; Yu, D R; Yu, J; Yu, J M; Yu, J; Yuan, L; Yuen, S P Y; Yusuff, I; Zabinski, B; Zaidan, R; Zaitsev, A M; Zakharchuk, N; Zalieckas, J; Zaman, A; Zambito, S; Zanello, L; Zanzi, D; Zeitnitz, C; Zeman, M; Zemla, A; Zeng, J C; Zeng, Q; Zengel, K; Zenin, O; Ženiš, T; Zerwas, D; Zhang, D; Zhang, F; Zhang, G; Zhang, H; Zhang, J; Zhang, L; Zhang, R; Zhang, R; Zhang, X; Zhang, Z; Zhao, X; Zhao, Y; Zhao, Z; Zhemchugov, A; Zhong, J; Zhou, B; Zhou, C; Zhou, L; Zhou, L; Zhou, M; Zhou, N; Zhu, C G; Zhu, H; Zhu, J; Zhu, Y; Zhuang, X; Zhukov, K; Zibell, A; Zieminska, D; Zimine, N I; Zimmermann, C; Zimmermann, S; Zinonos, Z; Zinser, M; Ziolkowski, M; Živković, L; Zobernig, G; Zoccoli, A; Nedden, M Zur; Zwalinski, L
2016-01-01
A search is performed for a heavy particle decaying into different flavour dilepton pairs ([Formula: see text], [Formula: see text] or [Formula: see text]), using 3.2 fb[Formula: see text] of proton-proton collision data at [Formula: see text] TeV collected in 2015 by the ATLAS detector at the Large Hadron Collider. No excess over the Standard Model prediction is observed. Limits at the 95 % credibility level are set on the mass of a [Formula: see text] boson with lepton-flavour-violating couplings at 3.0, 2.7 and 2.6 TeV, and on the mass of a supersymmetric [Formula: see text] sneutrino with R -parity-violating couplings at 2.3, 2.2 and 1.9 TeV, for [Formula: see text], [Formula: see text] and [Formula: see text] final states, respectively. The results are also interpreted as limits on the threshold mass for quantum black hole production.
Directory of Open Access Journals (Sweden)
Jinggang Chu
2015-05-01
Full Text Available River basin simulation and multi-reservoir optimal operation have been critical for river basin management. Due to the intense interaction between human activities and river basin systems, the river basin model and multi-reservoir operation model are complicated with a large number of parameters. Therefore, fast and stable optimization algorithms are required for river basin management under the changing conditions of climate and current human activities. This study presents a new global optimization algorithm, named as heuristic dynamically dimensioned search with sensitivity information (HDDS-S, to effectively perform river basin simulation and multi-reservoir optimal operation during river basin management. The HDDS-S algorithm is built on the dynamically dimensioned search (DDS algorithm; and has an improved computational efficiency while maintaining its search capacity compared to the original DDS algorithm. This is mainly due to the non-uniform probability assigned to each decision variable on the basis of its changing sensitivity to the optimization objectives during the adaptive change from global to local search with dimensionality reduced. This study evaluates the new algorithm by comparing its performance with the DDS algorithm on a river basin model calibration problem and a multi-reservoir optimal operation problem. The results obtained indicate that the HDDS-S algorithm outperforms the DDS algorithm in terms of search ability and computational efficiency in the two specific problems. In addition; similar to the DDS algorithm; the HDDS-S algorithm is easy to use as it does not require any parameter tuning and automatically adjusts its search to find good solutions given an available computational budget.
Search Engine Competition with Network Externalities
Argenton, C.; Prüfer, J.
2011-01-01
The market for Internet search is not only economically and socially important, it is also highly concentrated. Is this a problem? We study the question whether "competition is only a free click away". We argue that the market for Internet search is characterized by indirect network externalities
Content Based Searching for INIS
International Nuclear Information System (INIS)
Jain, V.; Jain, R.K.
2016-01-01
Full text: Whatever a user wants is available on the internet, but to retrieve the information efficiently, a multilingual and most-relevant document search engine is a must. Most current search engines are word based or pattern based. They do not consider the meaning of the query posed to them; purely based on the keywords of the query; no support of multilingual query and and dismissal of nonrelevant results. Current information-retrieval techniques either rely on an encoding process, using a certain perspective or classification scheme, to describe a given item, or perform a full-text analysis, searching for user-specified words. Neither case guarantees content matching because an encoded description might reflect only part of the content and the mere occurrence of a word does not necessarily reflect the document’s content. For general documents, there doesn’t yet seem to be a much better option than lazy full-text analysis, by manually going through those endless results pages. In contrast to this, new search engine should extract the meaning of the query and then perform the search based on this extracted meaning. New search engine should also employ Interlingua based machine translation technology to present information in the language of choice of the user. (author
Performance of clustering techniques for solving multi depot vehicle routing problem
Directory of Open Access Journals (Sweden)
Eliana M. Toro-Ocampo
2016-01-01
Full Text Available The vehicle routing problem considering multiple depots is classified as NP-hard. MDVRP determines simultaneously the routes of a set of vehicles and aims to meet a set of clients with a known demand. The objective function of the problem is to minimize the total distance traveled by the routes given that all customers must be served considering capacity constraints in depots and vehicles. This paper presents a hybrid methodology that combines agglomerative clustering techniques to generate initial solutions with an iterated local search algorithm (ILS to solve the problem. Although previous studies clustering methods have been proposed like strategies to generate initial solutions, in this work the search is intensified on the information generated after applying the clustering technique. Besides an extensive analysis on the performance of techniques, and their effect in the final solution is performed. The operation of the proposed methodology is feasible and effective to solve the problem regarding the quality of the answers and computational times obtained on request evaluated literature
Directory of Open Access Journals (Sweden)
Longquan Yong
2012-01-01
Full Text Available Harmony search (HS method is an emerging metaheuristic optimization algorithm. In this paper, an improved harmony search method based on differential mutation operator (IHSDE is proposed to deal with the optimization problems. Since the population diversity plays an important role in the behavior of evolution algorithm, the aim of this paper is to calculate the expected population mean and variance of IHSDE from theoretical viewpoint. Numerical results, compared with the HSDE, NGHS, show that the IHSDE method has good convergence property over a test-suite of well-known benchmark functions.
A metaheuristic for a numerical approximation to the mass transfer problem
Directory of Open Access Journals (Sweden)
Avendaño-Garrido Martha L.
2016-12-01
Full Text Available This work presents an improvement of the approximation scheme for the Monge-Kantorovich (MK mass transfer problem on compact spaces, which is studied by Gabriel et al. (2010, whose scheme discretizes the MK problem, reduced to solve a sequence of finite transport problems. The improvement presented in this work uses a metaheuristic algorithm inspired by scatter search in order to reduce the dimensionality of each transport problem. The new scheme solves a sequence of linear programming problems similar to the transport ones but with a lower dimension. The proposed metaheuristic is supported by a convergence theorem. Finally, examples with an exact solution are used to illustrate the performance of our proposal.
Directory of Open Access Journals (Sweden)
Yaniv Shani
2012-11-01
Full Text Available In three studies, we examined factors that may temporarily attenuate information search. People are generally curious and dislike uncertainty, which typically encourages them to look for relevant information. Despite these strong forces that promote information search, people sometimes deliberately delay obtaining valuable information. We find they may do so when they are concerned that the information might interfere with future pleasurable activities. Interestingly, the decision to search or to postpone searching for information is influenced not only by the value and importance of the information itself but also by well-being maintenance goals related to possible detrimental effects that negative knowledge may have on unrelated future plans.
Filter Pattern Search Algorithms for Mixed Variable Constrained Optimization Problems
National Research Council Canada - National Science Library
Abramson, Mark A; Audet, Charles; Dennis, Jr, J. E
2004-01-01
.... This class combines and extends the Audet-Dennis Generalized Pattern Search (GPS) algorithms for bound constrained mixed variable optimization, and their GPS-filter algorithms for general nonlinear constraints...
How to improve your PubMed/MEDLINE searches: 3. advanced searching, MeSH and My NCBI.
Fatehi, Farhad; Gray, Leonard C; Wootton, Richard
2014-03-01
Although the basic PubMed search is often helpful, the results may sometimes be non-specific. For more control over the search process you can use the Advanced Search Builder interface. This allows a targeted search in specific fields, with the convenience of being able to select the intended search field from a list. It also provides a history of your previous searches. The search history is useful to develop a complex search query by combining several previous searches using Boolean operators. For indexing the articles in MEDLINE, the NLM uses a controlled vocabulary system called MeSH. This standardised vocabulary solves the problem of authors, researchers and librarians who may use different terms for the same concept. To be efficient in a PubMed search, you should start by identifying the most appropriate MeSH terms and use them in your search where possible. My NCBI is a personal workspace facility available through PubMed and makes it possible to customise the PubMed interface. It provides various capabilities that can enhance your search performance.
Practical text mining and statistical analysis for non-structured text data applications
Miner, Gary; Hill, Thomas; Nisbet, Robert; Delen, Dursun
2012-01-01
The world contains an unimaginably vast amount of digital information which is getting ever vaster ever more rapidly. This makes it possible to do many things that previously could not be done: spot business trends, prevent diseases, combat crime and so on. Managed well, the textual data can be used to unlock new sources of economic value, provide fresh insights into science and hold governments to account. As the Internet expands and our natural capacity to process the unstructured text that it contains diminishes, the value of text mining for information retrieval and search will increase d
Categorization and Searching of Color Images Using Mean Shift Algorithm
Directory of Open Access Journals (Sweden)
Prakash PANDEY
2009-07-01
Full Text Available Now a day’s Image Searching is still a challenging problem in content based image retrieval (CBIR system. Most CBIR system operates on all images without pre-sorting the images. The image search result contains many unrelated image. The aim of this research is to propose a new object based indexing system Based on extracting salient region representative from the image, categorizing the image into different types and search images that are similar to given query images.In our approach, the color features are extracted using the mean shift algorithm, a robust clustering technique, Dominant objects are obtained by performing region grouping of segmented thumbnails. The category for an image is generated automatically by analyzing the image for the presence of a dominant object. The images in the database are clustered based on region feature similarity using Euclidian distance. Placing an image into a category can help the user to navigate retrieval results more effectively. Extensive experimental results illustrate excellent performance.
A Fuzzy Gravitational Search Algorithm to Design Optimal IIR Filters
Directory of Open Access Journals (Sweden)
Danilo Pelusi
2018-03-01
Full Text Available The goodness of Infinite Impulse Response (IIR digital filters design depends on pass band ripple, stop band ripple and transition band values. The main problem is defining a suitable error fitness function that depends on these parameters. This fitness function can be optimized by search algorithms such as evolutionary algorithms. This paper proposes an intelligent algorithm for the design of optimal 8th order IIR filters. The main contribution is the design of Fuzzy Inference Systems able to tune key parameters of a revisited version of the Gravitational Search Algorithm (GSA. In this way, a Fuzzy Gravitational Search Algorithm (FGSA is designed. The optimization performances of FGSA are compared with those of Differential Evolution (DE and GSA. The results show that FGSA is the algorithm that gives the best compromise between goodness, robustness and convergence rate for the design of 8th order IIR filters. Moreover, FGSA assures a good stability of the designed filters.
A Hybrid alldifferent-Tabu Search Algorithm for Solving Sudoku Puzzles
Directory of Open Access Journals (Sweden)
Ricardo Soto
2015-01-01
Full Text Available The Sudoku problem is a well-known logic-based puzzle of combinatorial number-placement. It consists in filling a n2 × n2 grid, composed of n columns, n rows, and n subgrids, each one containing distinct integers from 1 to n2. Such a puzzle belongs to the NP-complete collection of problems, to which there exist diverse exact and approximate methods able to solve it. In this paper, we propose a new hybrid algorithm that smartly combines a classic tabu search procedure with the alldifferent global constraint from the constraint programming world. The alldifferent constraint is known to be efficient for domain filtering in the presence of constraints that must be pairwise different, which are exactly the kind of constraints that Sudokus own. This ability clearly alleviates the work of the tabu search, resulting in a faster and more robust approach for solving Sudokus. We illustrate interesting experimental results where our proposed algorithm outperforms the best results previously reported by hybrids and approximate methods.
Directory of Open Access Journals (Sweden)
Rasim M. Alguliev
2011-01-01
Full Text Available Extractive multidocument summarization is modeled as a modified p-median problem. The problem is formulated with taking into account four basic requirements, namely, relevance, information coverage, diversity, and length limit that should satisfy summaries. To solve the optimization problem a self-adaptive differential evolution algorithm is created. Differential evolution has been proven to be an efficient and robust algorithm for many real optimization problems. However, it still may converge toward local optimum solutions, need to manually adjust the parameters, and finding the best values for the control parameters is a consuming task. In the paper is proposed a self-adaptive scaling factor in original DE to increase the exploration and exploitation ability. This paper has found that self-adaptive differential evolution can efficiently find the best solution in comparison with the canonical differential evolution. We implemented our model on multi-document summarization task. Experiments have shown that the proposed model is competitive on the DUC2006 dataset.
A Bee Colony Optimization Approach for Mixed Blocking Constraints Flow Shop Scheduling Problems
Directory of Open Access Journals (Sweden)
Mostafa Khorramizadeh
2015-01-01
Full Text Available The flow shop scheduling problems with mixed blocking constraints with minimization of makespan are investigated. The Taguchi orthogonal arrays and path relinking along with some efficient local search methods are used to develop a metaheuristic algorithm based on bee colony optimization. In order to compare the performance of the proposed algorithm, two well-known test problems are considered. Computational results show that the presented algorithm has comparative performance with well-known algorithms of the literature, especially for the large sized problems.
Riggs, Ken Roger
2002-01-01
Discusses problems with marking free text, text that is either natural language or semigrammatical but unstructured, that prevent well-formed XML from marking text for readily available meaning. Proposes a solution to mark meaning in free text that is consistent with the intended simplicity of XML versus SGML. (Author/LRW)
DEFF Research Database (Denmark)
Bose, Prosenjit; Fagerberg, Rolf; Howat, John
2016-01-01
We consider the problem of performing predecessor searches in a bounded universe while achieving query times that depend on the distribution of queries. We obtain several data structures with various properties: in particular, we give data structures that achieve expected query times logarithmic...
DEFF Research Database (Denmark)
Bose, Prosenjit; Fagerberg, Rolf; Howat, John
2014-01-01
We consider the problem of performing predecessor searches in a bounded universe while achieving query times that depend on the distribution of queries. We obtain several data structures with various properties: in particular, we give data structures that achieve expected query times logarithmic...
An interior-point method for the Cartesian P*(k-linear complementarity problem over symmetric cones
Directory of Open Access Journals (Sweden)
B Kheirfam
2014-06-01
Full Text Available A novel primal-dual path-following interior-point algorithm for the Cartesian P*(k-linear complementarity problem over symmetric cones is presented. The algorithm is based on a reformulation of the central path for finding the search directions. For a full Nesterov-Todd step feasible interior-point algorithm based on the new search directions, the complexity bound of the algorithm with small-update approach is the best-available bound.
Nearest Neighbor Search in the Metric Space of a Complex Network for Community Detection
Directory of Open Access Journals (Sweden)
Suman Saha
2016-03-01
Full Text Available The objective of this article is to bridge the gap between two important research directions: (1 nearest neighbor search, which is a fundamental computational tool for large data analysis; and (2 complex network analysis, which deals with large real graphs but is generally studied via graph theoretic analysis or spectral analysis. In this article, we have studied the nearest neighbor search problem in a complex network by the development of a suitable notion of nearness. The computation of efficient nearest neighbor search among the nodes of a complex network using the metric tree and locality sensitive hashing (LSH are also studied and experimented. For evaluation of the proposed nearest neighbor search in a complex network, we applied it to a network community detection problem. Experiments are performed to verify the usefulness of nearness measures for the complex networks, the role of metric tree and LSH to compute fast and approximate node nearness and the the efficiency of community detection using nearest neighbor search. We observed that nearest neighbor between network nodes is a very efficient tool to explore better the community structure of the real networks. Several efficient approximation schemes are very useful for large networks, which hardly made any degradation of results, whereas they save lot of computational times, and nearest neighbor based community detection approach is very competitive in terms of efficiency and time.
Memetic Algorithms to Solve a Global Nonlinear Optimization Problem. A Review
Directory of Open Access Journals (Sweden)
M. K. Sakharov
2015-01-01
Full Text Available In recent decades, evolutionary algorithms have proven themselves as the powerful optimization techniques of search engine. Their popularity is due to the fact that they are easy to implement and can be used in all areas, since they are based on the idea of universal evolution. For example, in the problems of a large number of local optima, the traditional optimization methods, usually, fail in finding the global optimum. To solve such problems using a variety of stochastic methods, in particular, the so-called population-based algorithms, which are a kind of evolutionary methods. The main disadvantage of this class of methods is their slow convergence to the exact solution in the neighborhood of the global optimum, as these methods incapable to use the local information about the landscape of the function. This often limits their use in largescale real-world problems where the computation time is a critical factor.One of the promising directions in the field of modern evolutionary computation are memetic algorithms, which can be regarded as a combination of population s