NDLI: Tailoring hyper-heuristics to specific instances of a scheduling problem using affinity and competence functions

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Empirical and analytical study of many-objective optimization problems: analysing distribution of nondominated solutions and population size for scalability of randomized heuristics

Memetic Computing : Volume 6, Issue 1, March 2014

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Tailoring hyper-heuristics to specific instances of a scheduling problem using affinity and competence functions

Content Provider	Springer Nature Link
Author	Salhi, Abdellah Vázquez Rodríguez, José Antonio
Copyright Year	2013
Abstract	Hyper-heuristics are high level heuristics which coordinate lower level ones to solve a given problem. Low level heuristics, however, are not all as competent/good as each other at solving the given problem and some do not work together as well as others. Hence the idea of measuring how good they are (competence) at solving the problem and how well they work together (their affinity). Models of the affinity and competence properties are suggested and evaluated using previous information on the performance of the simple low level heuristics. The resulting model values are used to improve the performance of the hyper-heuristic by tailoring it not only to the specific problem but the specific instance being solved. The test case is a hard combinatorial problem, namely the Hybrid Flow Shop scheduling problem. Numerical results on randomly generated as well as real-world instances are included.
Starting Page	77
Ending Page	84
Page Count	8
File Format	PDF
ISSN	18659284
Journal	Memetic Computing
Volume Number	6
Issue Number	2
e-ISSN	18659292
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2013-07-17
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Hybrid Flow Shop Scheduling Genetic Algorithm Hyper-heuristics ApplicationMathematics/Computational Methods of Engineering Artificial Intelligence (incl. Robotics) Statistical Physics, Dynamical Systems and Complexity Control, Robotics, Mechatronics Bioinformatics Applications of Mathematics
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Computer Science

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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