378 articles – 175 references  [version française]
HAL: hal-00661305, version 1

Short view  Export this paper
Scheduler-oriented algorithms to improve human-machine cooperation in transportation scheduling support systems
Gacias B., Cegarra J., Lopez P.
Engineering Applications of Artificial Intelligence 25, 4 (2012) p 801-813 - http://hal.archives-ouvertes.fr/hal-00661305
Article in peer-reviewed journal
Computer Science/Human-Computer Interaction
Computer Science/Operations Research
Cognitive science/Computer science
Scheduler-oriented algorithms to improve human-machine cooperation in transportation scheduling support systems
Bernat Gacias 1, Julien Cegarra () 2, Pierre Lopez (, http://homepages.laas.fr/lopez/) 3
1:  Centre d'Enseignement et de Recherche en Mathématiques et Calcul Scientifique (CERMICS)
http://cermics.enpc.fr/
Ecole des Ponts ParisTech
6 et 8 avenue Blaise Pascal Cité Descartes - Champs sur Marne 77455 Marne la Vallée Cedex 2
France
2:  Cognition, Langues, Langage, Ergonomie (CLLE)
http://w3.univ-tlse2.fr/clle/
CNRS : UMR5263 – Université Michel de Montaigne - Bordeaux III – Université Toulouse le Mirail - Toulouse II – Ecole Pratique des Hautes Etudes
Maison de La Recherche 5 Allées Antonio Machado 31058 TOULOUSE CEDEX 9
France
3:  Laboratoire d'analyse et d'architecture des systèmes (LAAS)
http://www.laas.fr
CNRS : UPR8001 – Université Paul Sabatier [UPS] - Toulouse III – Institut National Polytechnique de Toulouse - INPT – Institut National des Sciences Appliquées (INSA) - Toulouse
7 Av du colonel Roche 31077 TOULOUSE CEDEX 4
France
A decision support system designed to enhance human-machine interaction in transportation scheduling is proposed. We aim to integrate human factors and ergonomics from the beginning of the design phase and to propose a system fitted with enough flexibility to be able to deal with the characteristics of a dynamic context such as transportation scheduling. In this interdisciplinary approach, a link is done between problem solving methods (operations research techniques and data classification algorithms) and human-machine interaction (solving control modes). A set of scheduler-oriented algorithms favouring human-machine cooperation for problem solving is proposed. Some of these algorithms have been efficiently tested on instances of the literature. Finally, an original framework aiming to assist scheduler in constraint relaxation when the problem becomes infeasible is proposed and evaluated.
English

Engineering Applications of Artificial Intelligence
Publisher Elsevier
ISSN 0952-1976 
international
2012-06
25
4
p 801-813

Rapport LAAS n° 12028

Attached file list to this document: 
PDF
PaperEAAI.pdf(967.3 KB)