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International Journal of Applied Metaheuristic Computing (IJAMC)

Editor(s)-in-Chief: Peng-Yeng Yin (Ming Chuan University, Taiwan)
Published: Continuous Volume
Copyright: ©2010
DOI: 10.4018/IJAMC
ISSN: 1947-8283
EISSN: 1947-8291

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Description

The International Journal of Applied Metaheuristic Computing (IJAMC) is a rigorous refereed journal that publishes high quality, innovative research on the latest developments, models, and applications within the transdisciplinary fields related to metaheuristic computing. Providing researchers, practitioners, and academicians with insight into a wide range of topics such as genetic algorithms, differential evolution, and ant colony optimization, this journal contains useful articles for those seeking to learn, analyze, improve, and apply technologies within metaheuristic computing.

Volume 14, Issue 1

Volume 13, Issue 2

Volume 13, Issue 1

Volume 12, Issue 4

Volume 12, Issue 3

Volume 12, Issue 2

Volume 12, Issue 1

Volume 11, Issue 4

Volume 11, Issue 3

Volume 11, Issue 2

Volume 11, Issue 1

Volume 10, Issue 4

Volume 10, Issue 3

Volume 10, Issue 2

Volume 10, Issue 1

Volume 9, Issue 4

Volume 9, Issue 3

Volume 9, Issue 2

Volume 9, Issue 1

Volume 8, Issue 4

Volume 8, Issue 3

Volume 8, Issue 2

Volume 8, Issue 1

Volume 7, Issue 4

Volume 7, Issue 3

Volume 7, Issue 2

Volume 7, Issue 1

Volume 6, Issue 4

Volume 6, Issue 3

Volume 6, Issue 2

Volume 6, Issue 1

Volume 5, Issue 4

Volume 5, Issue 3

Volume 5, Issue 2

Volume 5, Issue 1

Volume 4, Issue 4

Volume 4, Issue 3

Volume 4, Issue 2

Volume 4, Issue 1

Volume 3, Issue 4

Volume 3, Issue 3

Volume 3, Issue 2

Volume 3, Issue 1

Volume 2, Issue 4

Volume 2, Issue 3

Volume 2, Issue 2

Volume 2, Issue 1

Volume 1, Issue 4

Volume 1, Issue 3

Volume 1, Issue 2

Volume 1, Issue 1

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Mission

The mission of International Journal of Applied Metaheuristic Computing (IJAMC) is to publish and disseminate original research on modeling, analysis, and applications in metaheuristic computing. The engineering and business problems the world faces today have become more impenetrable and unstructured, making the design of a satisfactory problem-specific algorithm nontrivial. Alternatively, researchers and practitioners look for generic metaheuristic computing that guides the course of a heuristic to search beyond the local optimality, which impairs the capability of traditional computation methods. Providing a forum for researchers, scientists, practitioners and students who wish to learn, analyze, improve and apply technologies in metaheuristic computing, IJAMC provides insights into all aspects of metaheuristic computing that take full advantage of higher level problem solving without a hassle to design problem-specific operations each time a new application appears.