Results 101 to 110 of about 7,821 (233)
Hierarchical Differentiable Fluid Simulation
Computer Graphics Forum, EarlyView.We introduce a two‐step algorithm that significantly reduces memory usage for solving control problems using differentiable fluid simulation techniques: our method first optimizes for bulk forces at reduced resolution, then refines local details over sub‐domains while maintaining differentiability. In trading runtime for memory, it enables optimization
Xiangyu Kong +4 more
wiley +1 more source
Automated generation of constructive ordering heuristics for educational timetabling [PDF]
, 2017 Construction heuristics play an important role in solving combinatorial optimization problems. These heuristics are usually used to create an initial solution to the problem which is improved using optimization techniques such as metaheuristics.
B McCollum +12 more
core +2 more sources
Adaptive Sampling for BRDF Acquisition
Computer Graphics Forum, EarlyView.We propose a data‐driven adaptive sampling strategy that predicts the optimal sampling pattern and count for BRDF acquisition from a single image, reducing capture time while preserving quality. Abstract The bidirectional reflectance distribution function (BRDF) describes the ratio of incoming radiance to outgoing radiance for all possible pairs of ...
Behnaz Kavoosighafi +3 more
wiley +1 more source
Gender, Work &Organization, EarlyView.ABSTRACT This paper interrogates the confessional foundations of Diversity, Equity, and Inclusion (DEI) work, which have emerged predominantly from Global North traditions rooted in Christian understandings of subjectivity. In such traditions, identity is asserted through self‐declaration, visibility, and vocal articulation of difference, what we term ...
Claudia Eger, Mustafa F. Özbilgin
wiley +1 more source
Knowledge discovery in hyper-heuristic using case-based reasoning on course timetabling [PDF]
, 2002 This paper presents a new hyper-heuristic method using Case-Based Reasoning (CBR) for solving course timetabling problems. The term Hyper-heuristics has recently been employed to refer to 'heuristics that choose heuristics' rather than heuristics that ...
Burke, Edmund +3 more
core +1 more source
Drone Squadron Optimization: a Self-adaptive Algorithm for Global Numerical Optimization
, 2017 This paper proposes Drone Squadron Optimization, a new self-adaptive metaheuristic for global numerical optimization which is updated online by a hyper-heuristic.
Banzhaf, Wolfgang +1 more
core +1 more source
Heuristic generation via parameter tuning for online bin packing [PDF]
, 2014 Online bin packing requires immediate decisions to be made for placing an incoming item one at a time into bins of fixed capacity without causing any overflow. The goal is to maximise the average bin fullness after placement of a long stream of items.
Asta, Shahriar +3 more
core +2 more sources
International Journal of Management Reviews, EarlyView.Abstract Leaders are widely positioned as cornerstones of neurodiversity inclusion within research and practice. Despite this, the management discipline remains plighted by lack of cohesive understanding regarding leadership in the context of neurodiversity—an issue only exacerbated by the fragmented nature of extant interdisciplinary research.
Mya Kirkwood +3 more
wiley +1 more source
A unified formulation for home healthcare routing and scheduling problems
International Transactions in Operational Research, EarlyView.Abstract Home Healthcare is an essential component of healthcare systems, where caregivers visit patients' homes to deliver services. While presenting advantages with respect to institutional care, such as being cost‐effective and alleviating family burdens, it presents challenges in scheduling and routing caregivers efficiently.
Sara Ceschia +7 more
wiley +1 more source
A Bi-objective Hyper-Heuristic Support Vector Machines for Big Data Cyber-Security
IEEE Access, 2018 Cyber security in the context of big data is known to be a critical problem and presents a great challenge to the research community. Machine learning algorithms have been suggested as candidates for handling big data security problems.
Nasser R. Sabar, Xun Yi, Andy Song
doaj +1 more source