Choice function based hyper-heuristics for multi-objective optimization
نویسندگان
چکیده
منابع مشابه
Choice function based hyper-heuristics for multi-objective optimization
A selection hyper-heuristic is a high level search methodology which operates over a fixed set of low level heuristics. During the iterative search process, a heuristic is selected and applied to a candidate solution in hand, producing a new solution which is then accepted or rejected at each step. Selection hyper-heuristics have been increasingly, and successfully, applied to single-objective ...
متن کاملA Choice Function based hyper-heuristic for Multi-objective Optimization
Hyper-heuristics are emerging methodologies that perform a search over the space of heuristics to solve difficult computational optimization problems. There are two main types of hyper-heuristics: selective and generative hyper-heuristics. An online selective hyper-heuristic framework manages a set of low level heuristics and aims to choose the best one at any given time using a performance mea...
متن کاملA multi-objective hyper-heuristic based on choice function
http://dx.doi.org/10.1016/j.eswa.2013.12.050 0957-4174/ 2014 Elsevier Ltd. All rights reserved. ⇑ Corresponding author. Tel.: +44 7873729666, +966 506620227. E-mail addresses: [email protected], [email protected] (M. Maashi), [email protected] (E. Özcan), graham.kendall@ nottingham.edu.my (G. Kendall). 1 Tel.: +6 (03) 8924 8306. Mashael Maashi a,⇑, Ender Özcan , Graham ...
متن کاملBuilding General Hyper-Heuristics for Multi-Objective Cutting Stock Problems
In this article we build multi-objective hyperheuristics (MOHHs) using the multi-objective evolutionary algorithm NSGA-II for solving irregular 2D cutting stock problems under a bi-objective minimization schema, having a trade-off between the number of sheets used to fit a finite number of pieces and the time required to perform the placement of these pieces. We solve this problem using a multi...
متن کاملDistributed Choice Function Hyper-heuristics for Timetabling and Scheduling
This paper investigates an emerging class of search algorithms, in which high-level domain independent heuristics, called hyperheuristics, iteratively select and execute a set of application specific but simple search moves, called low-level heuristics, working toward achieving improved or even optimal solutions. Parallel architectures have been designed and evaluated. Results based on a univer...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Applied Soft Computing
سال: 2015
ISSN: 1568-4946
DOI: 10.1016/j.asoc.2014.12.012