scispace - formally typeset
H

Huan Jin

Researcher at The University of Nottingham Ningbo China

Publications -  19
Citations -  126

Huan Jin is an academic researcher from The University of Nottingham Ningbo China. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 3, co-authored 14 publications receiving 47 citations. Previous affiliations of Huan Jin include Massachusetts Institute of Technology & University of Iowa.

Papers
More filters
Journal ArticleDOI

Exploring network effects of point-to-point networks: An investigation of the spatial patterns of Southwest Airlines’ network

TL;DR: Examining the spatial patterns of Southwest airlines' route network during Southwest's major network expansionary period for completing continental US geographic coverage between 1990 and 2006 helps predict how emerging LCC networks in other large aviation market, such as China, are likely to be developed over time if regulators give carriers reasonable freedom to develop their service network efficiently.
Journal ArticleDOI

Integer programming techniques for makespan minimizing workforce assignment models that recognize human learning

TL;DR: The techniques can be adapted to speed up the solution of most any makespan minimizing workforce assignment problem, and that large instances can be solved much faster than have previously been solved in the literature.
Journal ArticleDOI

Modeling biohydrogen production using different data driven approaches

TL;DR: In this paper, three modeling techniques namely multilayer perceptron artificial neural network (MLPANN), microbial kinetic with Levenberg-Marquardt algorithm (MKLMA) developed from microbial growth, and the response surface methodology (RSM) were used to investigate the biohydrogen (BioH2) process.
Posted Content

Analytics and Machine Learning in Vehicle Routing Research.

TL;DR: In this article, the authors present a comprehensive review of hybrid methods that combine analytical techniques with ML tools in addressing VRP problems, and conclude that ML can be beneficial in enhancing VRP modelling, and improving the performance of algorithms for both online and offline VRP optimisations.
Journal ArticleDOI

Workforce grouping and assignment with learning-by-doing and knowledge transfer

TL;DR: A workforce allocation problem in which workers learn both by performing a job and by observing the performance of and interacting with co-located colleagues is considered, which can benefit from both effectively assigning individuals to jobs and grouping workers into teams.