Results 21 to 30 of about 3,855 (254)
IET Networks, EarlyView., 2022 Abstract Everything can be connected in the Internet of Things (IoTs) technology that enables efficient communication between connected objects. IoTs industry‐based meta‐heuristic and mining algorithms, which are considered an important field of Artificial Intelligence will be used to construct a healthcare application in this study for lowering costs,
Muhaned Al‐Hashimi +4 more
wiley +1 more source
University Course Timetabling Using Graph-based Hyper Heuristics [PDF]
مدیریت صنعتی, 2013 University course timetabling is a complex optimizationproblem. There are many components like departments, faculties, rooms,and students making the problem huge and difficult to solve.
Khodakaram Salimifard +2 more
doaj +1 more source
Ensemble move acceptance in selection hyper-heuristics [PDF]
, 2016 Selection hyper-heuristics are high level search methodologies which control a set of low level heuristics while solving a given problem. Move acceptance is a crucial component of selection hyper-heuristics, deciding whether to accept or reject a new ...
Kheiri, Ahmed +2 more
core +1 more source
A comparison of crossover control mechanisms within single-point selection hyper-heuristics using HyFlex [PDF]
, 2015 Hyper-heuristics are search methodologies which operate at a higher level of abstraction than traditional search and optimisation techniques. Rather than operating on a search space of solutions directly, a hyper-heuristic searches a space of low-level ...
Burke, Edmund K. +2 more
core +1 more source
Constructing constrained-version of magic squares using selection hyper-heuristics [PDF]
, 2013 A square matrix of distinct numbers in which every row, column and both diagonals have the same total is referred to as a magic square. Constructing a magic square of a given order is considered a difficult computational problem, particularly when ...
Kheiri, Ahmed, Özcan, Ender
core +6 more sources
Selection hyper-heuristics in dynamic environments [PDF]
Journal of the Operational Research Society, 2013 Current state-of-the-art methodologies are mostly developed for stationary optimization problems. However, many real-world problems are dynamic in nature, where different types of changes may occur over time. Population-based approaches, such as evolutionary algorithms, are frequently used for solving dynamic environment problems.
Berna Kiraz +2 more
openaire +2 more sources
Applied Computer Systems, 2022 A problem of minimizing the total weighted tardiness in the preemptive single machine scheduling for discrete manufacturing is considered. A hyper-heuristic is presented, which is composed of 24 various heuristics, to find an approximately optimal ...
Romanuke Vadim
doaj +1 more source
Sequence-Based Selection Hyper-Heuristic Model via MAP-Elites
IEEE Access, 2021 Although the number of solutions in combinatorial optimization problems (COPs) is finite, some problems grow exponentially and render exact approaches unfeasible. So, approximate methods, such as heuristics, are customary.
Melissa Sanchez +3 more
doaj +1 more source
Searching the Hyper-heuristic Design Space [PDF]
Cognitive Computation, 2013 We extend a previous mathematical formulation of hyper-heuristics to reflect the emerging generalization of the concept. We show that this leads naturally to a recursive definition of hyper-heuristics and to a division of responsibility that is suggestive of a blackboard architecture, in which individual heuristics annotate a shared workspace with ...
Jerry Swan +4 more
openaire +3 more sources
An Investigation of Hybrid Framework for Dynamic Multi Objective Problems
Gazi Üniversitesi Fen Bilimleri Dergisi, 2018 Multi-objective evolutionary algorithms and selection hyper-heuristics are adaptive methods that can handle different types of dynamism which may occur in the environment.
Berna KİRAZ
doaj +1 more source