Results 51 to 60 of about 715 (165)
A multi-objective hyper-heuristic based on choice function [PDF]
, 2014 Hyper-heuristics are emerging methodologies that perform a search over the space of heuristics in an attempt to solve difficult computational optimization problems.
Kendall, Graham +2 more
core +2 more sources
IET Collaborative Intelligent Manufacturing, Volume 7, Issue 1, January/December 2025.The stochastic flowshop scheduling problem is addressed. An ML‐method to speed up the local search is proposed. ABSTRACT In this paper, we address a stochastic variant of the well‐known permutation flowshop scheduling problem, where the processing times of the jobs in the machines are assumed to be random variables.
Jose M. Framinan
wiley +1 more source
Application of population evolvability in a hyper-heuristic for dynamic multi-objective optimization
Technological and Economic Development of Economy, 2019 It is important to know the properties of an optimization problem and the difficulty an algorithm faces to solve it. Population evolvability obtains information related to both elements by analysing the probability of an algorithm to improve current ...
Teodoro Macias-Escobar +5 more
doaj +1 more source
On the Machine Learning Techniques for Side-channel Analysis [PDF]
, 2016 Side-channel attacks represent one of the most powerful category of attacks on cryptographic devices with profiled attacks in a prominent place as the most powerful among them.
Guilley, Sylvain +2 more
core
Fuzzy adaptive parameter control of a late acceptance hyper-heuristic [PDF]
, 2014 A traditional iterative selection hyper-heuristic which manages a set of low level heuristics relies on two core components, a method for selecting a heuristic to apply at a given point, and a method to decide whether or not to accept the result of the ...
Jackson, Warren G. +2 more
core +2 more sources
IET Cyber-Physical Systems: Theory &Applications, Volume 10, Issue 1, January/December 2025.This systematic analysis aims to offer a unique point to researchers and facilitates this process by allowing researchers to benchmark and compare various techniques, evaluate their effectiveness and establish best practices. It provides evidence‐based insights into optimal strategies for implementation while addressing potential trade‐offs in ...
Kai Hung Tang +4 more
wiley +1 more source
Computer-Aided Civil and Infrastructure Engineering, Volume 39, Issue 20, Page 3103-3124, 15 October 2024.Abstract U‐shaped automated container terminals (ACTs) represent a strategic design in port infrastructure that facilitates simultaneous loading and unloading operations. This paper addresses the challenges of scheduling multiple types of equipment, such as dual trolley quay cranes (DTQCs), automated guided vehicles (AGVs), double cantilever rail ...
Xiang Zhang +3 more
wiley +1 more source
An iterated multi-stage selection hyper-heuristic [PDF]
, 2015 There is a growing interest towards the design of reusable general purpose search methods that are applicable to different problems instead of tailored solutions to a single particular problem. Hyper-heuristics have emerged as such high level methods that
Ahmed Kheiri +44 more
core +4 more sources
IET Collaborative Intelligent Manufacturing, Volume 6, Issue 3, September 2024.The authors introduce the distributed parallel assembly permutation flow shop scheduling problem, aiming to enhance collaborative production efficiency among multiple factories in a networked environment. A mathematical model is established and an improved hybrid distribution estimation algorithm is proposed to minimise the makespan.
Lizhen Du +4 more
wiley +1 more source
An apprenticeship learning hyper-heuristic for vehicle routing in HyFlex [PDF]
, 2014 Apprenticeship learning occurs via observations while an expert is in action. A hyper-heuristic is a search method or a learning mechanism that controls a set of low level heuristics or combines different heuristic components to generate heuristics for ...
Asta, Shahriar, Özcan, Ender
core +2 more sources