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Topic: Metaheuristic

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	Metaheuristic - Wikipedia, the free encyclopedia
		A metaheuristic is a heuristic method for solving a very general class of computational problems by combining user given fl-box procedures — usually heuristics themselves — in a hopefully efficient way.
		Metaheuristics are generally applied to problems for which there is no satisfactory problem-specific algorithm or heuristic; or when it is not practical to implement such a method.
		In spite of overly-optimistic claims by some of their advocates, metaheuristics are not a panacea, and their indiscriminate use often is much less efficient than even the crudest problem-specific heuristic, by several orders of magnitude.
	en.wikipedia.org /wiki/Metaheuristic (1286 words)

	Call for Papers
		Metaheuristics, such as simulated annealing, genetic and evolutionary algorithms, tabu search, ant colony optimization, scatter search and iterated local search, have received considerable interest in the fields of applied artificial intelligence and combinatorial optimization.
		It is implicit with the subject of the special issue that contributions should address the combination and comparison of different metaheuristic components and concepts.
		In contrast to standard research in metaheuristics, also negative results - e.g., a component shows poor performance for the majority of test instances - are of considerable importance in hybridization.
	www.ifors.org /panorama/callfp/list/call_14_04.shtml (554 words)

	Genetic Algorithms
		A metaheuristic technique is a top-level general strategy which guides other heuristics to search for feasible solutions in complex solution spaces.
		Metaheuristics have been generally applied to problems classified as NP-Hard or NP-Complete by the theory of computational complexity.
		However, metaheuristics would also be applied to other combinatorial optimization problems for which it is known that a polynomial-time solution exists but is not practical.
	www.personal.psu.edu /faculty/w/x/wxc28/swarmcourse.htm (1080 words)

	Metaheuristics Network
		The overall goal of the Metaheuristics Network is to increase our understanding of metaheuristics, to propose new ways of structuring metaheuristic components, and to evaluate their contribution to metaheuristics behavior as well as to use the extracted information for the development of new hybrid metaheuristics.
		Other scientific goals are the definition of new high-performing hybrid metaheuristics, that is, metaheuristics that combine components taken from existing metaheuristics, as well as the definition and use of a strictly controlled, machine independent, experimental methodology which allows a fair and meaningful comparison of experimental results.
		Each network node implements the metaheuristic for which it is an expert, and a second metaheuristic chosen by the co-ordinator (the co-ordinator will choose the second metaheuristic in such a way that each node will implement each metaheuristic for at least one problem).
	iridia.ulb.ac.be /~meta/newsite/index.php?main=1 (964 words)

	Project-Team-DOLPHIN:Hybrid multi-objective optimization methods
		The success of metaheuristics is based on their ability to find efficient solutions in a reasonable time [54].
		It is now necessary to generalize metaheuristic hybridization and to propose adaptive hybrid models that may evolve during the search while selecting the appropriate metaheuristic.
		It could be also interesting to study the robustness of the different parallel models (in particular in the multi-objective case) and to propose rules that determine, given a specific problem, which kind of parallelism to use.
	www.inria.fr /rapportsactivite/RA2005/dolphin/uid26.html (1292 words)

	Mining Genomic Data with Metaheuristic Techniques
		Research in the GISUM group at the University of Málaga is investigating the use of evolutionary metaheuristics for this purpose.
		The pace at which research currently occurs is affecting most fields of science, not least the rapidly developing areas of molecular biology and genomics.
		In the second approach, modern heuristic techniques (metaheuristics) are employed to produce probably (though not yet provably) optimal solutions for these problems.
	www.ercim.org /publication/Ercim_News/enw60/cotta.html (869 words)

	Download Open Metaheuristic 0.3 for Linux - Open Metaheuristic (oMetah) is a library aimed at the conception of ...
		Open Metaheuristic (oMetah) is a library aimed at the conception of metaheuristics (i.e.
		Open Metaheuristic library follows the "adaptive learning search" approach in the design of metaheuristics (an approach inspired from the "adaptive memory programming").
		You can easily add your own metaheuristic and test it on the implemented problems, or add your own problem, and use the implemented metaheuristics to solve it.
	linux.softpedia.com /get/Programming/Libraries/Open-Metaheuristic-7952.shtml (242 words)

	metaheuristic (Site not responding. Last check: 2007-10-22)
		Metaheuristics have been most generally applied to problems classified as NP-Hard or NP-Complete by the theory of computational complexity.
		However, metaheuristics would also be applied to other combinatorial optimisation problems for which it is known that a polynomial-time solution exists but is not practical.
		Examples of metaheuristics are Tabu Search, simulated annealing, genetic algorithms and memetic algorithms.
	burks.bton.ac.uk /burks/foldoc/70/72.htm (93 words)

	YOR12 Conference
		Heuristic and metaheuristic approaches have proved to be a very effective tool for finding good approximate solutions for difficult scheduling and optimisation problems arising in industrial, economic, and scientific domains.
		The metaheuristic stream at YOR12 is open to all of these heuristic and metaheuristic approaches for solving real life applications as well as combinatorial optimisation problems.
		The concept of a hyperheuristic is introduced as an approach that operates at a higher lever of abstraction than current metaheuristic approaches by heuristically managing the choice as to which of several lower-level solution methods should be applied, depending upon the characteristics of the region of the solution space currently under exploration.
	www.orsoc.org.uk /conf/previous/yor12/streams/yor12_metaheuristics.htm (1181 words)

	Metaheuristics Network
		The Metaheuristics Network is a project sponsored by the Improving Human Potential program of the European Community (HPRN-CT-1999-00106).
		The activities of the Metaheuristics Network, coordinated by Prof.
		A number of publications were produced: 2 books, 4 edited books, 3 book chapters, 33 journal articles, 1 journal special issue, 63 conference papers, and 32 technical reports.
	www.metaheuristics.org (67 words)

	Main Page - Open Metaheuristics
		It follows the "adaptive learning search" approach in the design of metaheuristics (an approach inspired from the "adaptive memory programming").
		One of the main goal of oMetah is to permit rigourous empirical tests of metaheuristics, through a statistical approach.
		Open Metaheuristic is a free software, licensed under the GNU Lesser General Public License (LGPL).
	ometah.berlios.de (779 words)

	Second International Workshop on Hybrid Metaheuristics (HM 2005)
		This Call for Papers is also available as a flyer.
		It is implicit with the subject of the workshop that contributions should address the combination and comparison of different metaheuristic components and concepts.
		Such results have often been ignored, at least in the publication of results in standard metaheuristics research.
	www.lsi.upc.edu /~hm2005/cfp.html (944 words)

	Automated Software Testing with Metaheuristic Techniques
		In our work, we have automated the test case generation by means of two metaheuristic search techniques called Tabu Search and Scatter Search, which had not been used for this kind of problems yet.
		We have developed two different algorithms that explore the program control flow graph (whose nodes represent statements and whose edges represent the flow of control between statements) to determine the test cases that attain the desired code coverage.
		Tabu Search is a metaheuristic search technique based on that of the next k neighbours, while maintaining a tabu list (memory) that avoids repeating the search in the same area of the solution space.
	www.ercim.org /publication/Ercim_News/enw58/diaz_e.html (808 words)

	BioMed Central \| Abstract \| 1471-2105-7-483 \| Novel metaheuristic for parameter estimation in nonlinear dynamic ...
		In this contribution, we describe and apply this novel metaheuristic, inspired by recent developments in the field of operations research, to a set of complex identification problems and we make a critical comparison with respect to the previous (above mentioned) successful methods.
		The new metaheuristic presented in this paper aims to ensure the proper solution of these problems by adopting a global optimization approach, while keeping the computational effort under reasonable values.
		This new metaheuristic was applied to a set of three challenging parameter estimation problems of nonlinear dynamic biological systems, outperforming very significantly all the methods previously used for these benchmark problems.
	www.biomedcentral.com /1471-2105/7/483/abstract (355 words)

	SEMINAL Network Software Engineering with Metaheuristic INnovative ALgorithms
		The SEMINAL team believes that similar approaches can be applied more widely to a whole range of Software Engineering problems such as the balancing of trade-offs in multi-faceted requirements documents, the mapping and distribution of a design to an optimal software architecture, the execution of sufficient regression tests after system modification and user interface personalization.
		The SEMINAL team aims mainly to encourage the application of Metaheuristic Algorithms to the solution of a wide range of Software Engineering problems, rather than develop the theory of Metaheuristic Algorithms.
		However, it is felt that a more formal arrangement would serve to cement the existing embryonic ties and would provide a springboard for the formation of a new and important research community within the general area of Software Engineering.
	homepages.gold.ac.uk /mark/seminal/index.html (1721 words)

	Meta Heuristic (Site not responding. Last check: 2007-10-22)
		A MetaHeuristic is a semi-mythical method for finding good heuristics for particular problems.
		A metaheuristic is a pretty good rule for finding pretty good rules.
		One of the most important things to remember about metaheuristics is that there's NoFreeLunch.
	c2.com /cgi/wiki?MetaHeuristic (231 words)

	metaheuristic - OneLook Dictionary Search
		Tip: Click on the first link on a line below to go directly to a page where "metaheuristic" is defined.
		metaheuristic : Dictionary of Algorithms and Data Structures [home, info]
		metaheuristic : FOLDOP - Free On Line Dictionary Of Philosophy [home, info]
	www.onelook.com /cgi-bin/cgiwrap/bware/dofind.cgi?word=metaheuristic (99 words)

	International Journal of Emerging Electric Power Systems
		The original GEP problem is modified using the proposed methods i) Virtual Mapping Procedure (VMP), and ii) Penalty Factor Approach (PFA), to improve the effectiveness of the Metaheuristic techniques.
		The results of the metaheuristic techniques are compared and validated with that of Dynamic Programming (DP).
		The performances of each metaheuristic technique were compared in terms of their Success Rate (SR), Average Number of Generations (ANG), the error percentage and the mean execution time.
	www.bepress.com /ijeeps/vol6/iss1/art2 (243 words)

	An interactive evolutionary metaheuristic for multiobjective combinatorial optimization. Management Science - Find ... (Site not responding. Last check: 2007-10-22)
		An interactive evolutionary metaheuristic for multiobjective combinatorial optimization.
		The complexity of single-objective combinatorial problems increasingly leads practitioners of management science to employ metaheuristics such as simulated annealing, tabu search, or genetic algorithms.
		For multiobjective problems, the complexity in question is compounded by the existence of trade-offs between different objectives, which must be evaluated in terms of the preferences of a given decision maker (DM).
	www.findarticles.com /p/articles/mi_go2267/is_200312/ai_n9721519 (166 words)

	Glover, Fred W.; Kochenberger, Gary A.; Glover, Fred W.: Handbook of Metaheuristics (Site not responding. Last check: 2007-10-22)
		The Handbook of Metaheuristics provides both the research and practitioner communities with a comprehensive coverage of the metaheuristic methodologies that have proven to be successful in a wide variety of real-world problem settings.
		Moreover, it is these metaheuristic strategies that hold particular promise for success in the future.
		This family of metaheuristic chapters provides a state-of-the-art, comprehensive coverage of the major topics and methodologies of modern metaheuristics.
	www.forbesbookclub.com /bookpage.asp?prod_cd=IGT40 (258 words)

	ASAP Research Themes: Heuristics and Metaheuristics (Site not responding. Last check: 2007-10-22)
		To explore a variety of metaheuristics approaches to solve complex combinatorial optimisation problems.
		Since ASAP's formation in 1996, the investigation of metaheuristic methods has played a major role in our research strategy.
		We continue to use and explore metaheuristics (and hybrids) to solve a wide range of complex real world problems.
	www.asap.cs.nott.ac.uk /themes/hmh.shtml (77 words)

	CiteULike: Ant Colony Optimization: A New Meta-Heuristic (Site not responding. Last check: 2007-10-22)
		This article presents an overview of recent work on ant algorithms, that is, algorithms for discrete optimization that took inspiration from the observation of ant colonies' foraging behavior, and introduces the ant colony optimization (ACO) metaheuristic.
		In the first part of the article the basic biological findings on real ants are reviewed and their artificial counterparts as well as the ACO metaheuristic are defined.
		In the second part of the article a number of applications of ACO...
	www.citeulike.org /user/ddahlem/article/149344 (219 words)

	MLS+CP: Workshop on Combination of metaheuristic and local search with Constraint Programming techniques
		Constraint programming and metaheuristics share the same objective at offering effective tools to aid decision makers in solving real-life problems.
		It will be possible in the first place to express most of the existing strategies and in the second place to build (manually or automatically) new ones.
		In a second part, we present, as an illustration, the methods that we have proposed to adapt some metaheuristics : simulated annealing, tabu search, genetic algorithms and ant colony algorithms.
	ppcro.free.fr /mlscp.html (1528 words)

	Automated Software Testing Using a Metaheuristic Technique Based on Tabu Search (Site not responding. Last check: 2007-10-22)
		The use of techniques for automating the generation of software test cases is very important as it can reduce the time and cost of this process.
		The latest methods for automatic generation of tests use metaheuristic search techniques, i.e.
		There is a great deal of research into the use of Genetic Algorithms to obtain a specific coverage in software testing but there is none using the metaheuristic Tabu Search technique.
	csdl.computer.org /comp/proceedings/ase/2003/2035/00/20350310abs.htm (198 words)

	CiteULike: Tag optimization (Site not responding. Last check: 2007-10-22)
		On the effectiveness of incorporating randomness and memory into a multi-start metaheuristic with application to the Set Covering Problem
		posted to continuous metaheuristic nelder-mead optimization tabu-search by nojhan as
		posted to constraints continuous evolutionary-computation genetic-algorithm metaheuristic optimization by nojhan as
	www.citeulike.org /tag/optimization (806 words)

	Open Metaheuristic (Site not responding. Last check: 2007-10-22)
		It follows the « adaptive memory programming » approach in the design of metaheuristics.
		It is mainly designed to handle continuous or mixed-integer problems, often met in engineering applications.
		Open Metaheuristic is a free software (free, as in freedom, not only open-source), licensed under the GNU Lesser General Public License (LGPL).
	www.nongnu.org /ometah (230 words)

	Abstract - Metaheuristic Optimization with Evolver, Genocop and OptQuest
		Even though the most effective solution procedure for a problem is a customized optimization method, a good general-purpose optimizer can also be effective and much more economical.
		This paper examines and compares three general-purpose, metaheuristic optimizers: Evolver, Genocop, and OptQuest.
		Evolver is a commercial genetic-algorithm add-in for Microsoft Excel.
	www.decisioneering.com /optquest/comparisons.html (103 words)

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