Results 71 to 80 of about 3,855 (254)
Non-linear great deluge with learning mechanism for solving the course timetabling problem [PDF]
, 2009 International ...
Landa-Silva, D. +3 more
core +1 more source
Automated construction of evolutionary algorithm operators for the bi-objective water distribution network design problem using a genetic programming based hyper-heuristic approach [PDF]
, 2015 The water distribution network (WDN) design problem is primarily concerned with finding the optimal pipe sizes that provide the best service for minimal cost; a problem of continuing importance both in the UK and internationally.
Keedwell, Edward +3 more
core +1 more source
Tetrazine Ligation in Living Systems: Beyond Fast Kinetics to Effective Bioorthogonality
Chemistry – A European Journal, EarlyView.Rapid reaction kinetics (k2) alone do not ensure successful tetrazine ligation in living systems. This review introduces ‘effective orthogonality’—focusing on chemical survival, availability, and encounter—as a practical framework. We highlight how bottlenecks shift from cellular sinks to in vivo delivery limits, offering design strategies for reliable
Junhyeong Yim +3 more
wiley +1 more source
South African Computer Journal, 2012 Hyper-heuristics are aimed at providing a generalized solution to optimization problems rather than producing the best result for one or more problem instances.
Nelishia Pillay
doaj
Hybridising heuristics within an estimation distribution algorithm for examination timetabling [PDF]
, 2015 This paper presents a hybrid hyper-heuristic approach based on estimation distribution algorithms. The main motivation is to raise the level of generality for search methodologies.
A Soghier +21 more
core +2 more sources
Cytometry Part B: Clinical Cytometry, EarlyView.Abstract Our knowledge of the immune system continues to expand at a rapid pace, and this coupled with technological advances now enables us to interrogate both the breadth and the depth of the immune response at levels without precedent. This has also facilitated rapidly integrating some of this carefully vetted knowledge into clinical practice ...
Aaruni Khanolkar, Aisha Ahmed
wiley +1 more source
Offline Learning for Selection Hyper-heuristics with Elman Networks [PDF]
, 2017 This is the author accepted manuscript. The final version is available from the publisher via the link in this record.Offline selection hyper-heuristics are machine learning methods that are trained on heuristic selections to create an algorithm that is ...
Keedwell, E, Yates, W
core
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
Human Resource Development Quarterly, EarlyView.ABSTRACT This study explores incidental learning among physicians navigating uncertainty during the COVID‐19 pandemic. Using a constructivist research design, we conducted a literature review of 13 empirical studies on incidental learning in complexity and analyzed critical incident interviews with 12 emergency medicine and intensive care physicians ...
Henriette Lundgren +4 more
wiley +1 more source
Online Selection of CMA-ES Variants
, 2019 In the field of evolutionary computation, one of the most challenging topics is algorithm selection. Knowing which heuristics to use for which optimization problem is key to obtaining high-quality solutions. We aim to extend this research topic by taking
Bäck, Thomas +3 more
core +1 more source