Implications of technological changes in vehicle routing interfaces for planners' constraint processing

International audienceThis study sought to assess the consequences of technological changes in vehicle routing interfaces for planners' constraint processing during route selection. We began by developing a model of domain constraints for the generic vehicle routing problem, in order to characterize planners' constraint processing and assess the visibility of constraints on different routing interfaces. An experiment featuring vehicle routing problems was then designed to test interfaces reflecting technological changes, including automation leading to simplified interfaces and the display of multiple routes computed by algorithms. Twelve participants who had worked for a small transport company for nine months were exposed to all these interfaces. Mental workload, performance and decision-making times were measured. Results revealed that automation decreases mental workload and decision times, attributable to the abridged (vs. unabridged) display of constraints on the interface. Results also showed that the perceptual (vs. analytical) display of routes greatly decreases decision times and enhances performances

Analyse du domaine de travail pour les problèmes de tournées de véhicules

Cet article s'inscrit dans une démarche de proposition d'une approche interdisciplinaire appliquée à la logistique des transports. On s'intéresse plus particulièrement à la conception d'une architecture générique pour le problème de tournées de véhicules (VRP). On propose ainsi une articulation entre des méthodes de recherche opérationnelle (principalement la programmation par contraintes) et une analyse du domaine de travail issue de l'ergonomie cognitive

Scheduler-oriented algorithms to improve human-machine cooperation in transportation scheduling support systems

International audienceA 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

An interdisciplinary method for a generic vehicle routing problem decision support system

International audienceIn this paper, we propose an interdisciplinary method for the logistics of transportation. It focuses on the design of a generic architecture for the vehicle routing problem (VRP). We highlight that human factors and dynamics aspects are generally ignored in the classical approaches to solve the vehicle routing problem. In our study, a link is done between methods of operations research (specific methods to solve vehicle routing problems and constraint programming techniques) and a work domain analysis technique coming from cognitive ergonomics. The proposed architecture allows to consider and to process the constraints identified by the work domain analysis during the problem resolution. It is also well adapted to the consideration of the Human as a main actor in the decision-making process

Work domain analysis and ecological interface for the vehicle routing problem

International audienceIn this paper, we propose a work domain analysis for the vehicle routing problem. This analysis facilitates the identification of the problem constraints. The analysis is done through an abstraction hierarchy which facilitates an ecological user-interface design. The proposed decision support system and the ecological interfaces are presented. Finally, we propose an experimental study in order to evaluate the influence on the user for one of these interfaces

A decision support system for vehicle routing based on model inversion and data analysis

International audienceIn this paper, we present a three-phase solving mechanism for the vehicle routing problem. The solving mechanism is part of a decision support system architecture deduced from an interdisciplinary study. We highlight that human factors and dynamic aspects are generally ignored in the classical approaches to solve the problem. In our approach, a link is done between methods of operations research and an ecological interface design coming from cognitive ergonomics. We focus our study in how to manage the constraint relaxation if the problem is not satisfiable. We propose and evaluate model inversion techniques and data classification based methods in order to determine the most suitable constraints to relax in priority

OpenMATB: A Task Battery promoting task customization, software extensibility and experiment replicability

The original Multi-Attribute Task Battery (MATB) contains a set of interactive tasks that are representative of those performed during aircraft piloting (Comstock & Arnegard, 1992). More precisely, it requires participants to simultaneously perform four tasks that are distributed over the screen: a system monitoring task, a compensatory tracking task, an auditory communication task and a resource management task. MATB task set offers a robust way to study the effects of various parameters (e.g., automation, priorities, instructions and so on) on the participant’s multitasking behavior, such as his/her decision-making, level of performance, ocular behavior, mental workload, and so on. Moreover, the nature of the reduction allows researchers to design experiments that can be used even with participants having no prior experience of aircraft. This probably explains why, since it was first published, MATB has undoubtedly become one of the most firmly established micro-world used by human factors researchers. However, as thirty years have passed since the original MATB it appears no longer adequate to meet up-to-date research requirements. Multiple incompatible re-implementations have been designed, such as MATB-II (Santiago-Espada, Myer, Latorella, & Comstock, 2011), AF-MATB (Miller, 2010), or TSU-MATB (Thanoon, Zein-Sabatto, & McCurry, 2017)

Differences in Multitask Resource Reallocation After Change in Task Values

International audienceObjective The objective was to characterize multitask resource reallocation strategies when managing subtasks with various assigned values.Background When solving a resource conflict in multitasking, Salvucci and Taatgen predict a globally rational strategy will be followed that favors the most urgent subtask and optimizes global performance. However, Katidioti and Taatgen identified a locally rational strategy that optimizes only a subcomponent of the whole task, leading to detrimental consequences on global performance. Moreover, the question remains open whether expertise would have an impact on the choice of the strategy.Method We adopted a multitask environment used for pilot selection with a change in emphasis on two out of four subtasks while all subtasks had to be maintained over a minimum performance. A laboratory eye-tracking study contrasted 20 recently selected pilot students considered as experienced with this task and 15 university students considered as novices.Results When two subtasks were emphasized, novices focused their resources particularly on one high-value subtask and failed to prevent both low-value subtasks falling below minimum performance. On the contrary, experienced people delayed the processing of one low-value subtask but managed to optimize global performance.Conclusion In a multitasking environment where some subtasks are emphasized, novices follow a locally rational strategy whereas experienced participants follow a globally rational strategy.Application During complex training, trainees are only able to adjust their resource allocation strategy to subtask emphasis changes once they are familiar with the multitasking environment

Perspectives ergonomiques sur la santé : Vers un système de santé capacitant

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The Role of Algorithm and Result Comprehensibility of Automated Scheduling on Complacency

International audienceSeveral studies have stressed that even expert operators who are aware of a machine's limits could adopt its proposals without questioning them (i.e., the complacency phenomenon). In production scheduling for manufacturing, this is a significant problem, as it is often suggested that the machine be allowed to build the production schedule, confining the human role to that of rescheduling. This article evaluates the characteristics of scheduling algorithms on human rescheduling performance, the quality of which was related to complacency. It is suggested that scheduling algorithms be characterized as having result comprehensibility (the result respects the scheduler's expectations in terms of the discourse rules of the information display) or algorithm comprehensibility (the complexity of the algorithm hides some important constraints). The findings stress, on the one hand, that result comprehensibility is necessary to achieve good production performance and to limit complacency. On the other hand, algorithm comprehensibility leads to poor performance due to the very high cost of understanding the algorithm