On the utility of experiential cross-training for team decision-making under time stress

This study investigated the effectiveness of experiential cross-training in a team context for team decision-making under time stress in a simulated naval surveillance task. It was hypothesized that teams whose members explicitly experience all team positions will perform better under time pressure due to a better shared Team Interaction Model (Cannon-Bowers et al. 1993). In addition, it was posited that experiential cross-training would reduce the negative effect of member reconfiguration that can occur in certain military situations. Three groups of teams participated in this study (cross-trained, reconfigured and control). The experiment involved three team training sessions, followed by three time-stressed exercise sessions. During training, one group of teams was cross-trained (CT) by asking each member to perform an entire session at each of the three team positions. Member reconfiguration (where each member was shifted to another's position) was unexpectedly introduced at the first of the exercise sessions for the CT group and for another group (reconfigured) that had not been cross-trained. A third (control) group was neither cross-trained nor reconfigured. During training, the performance of non-CT teams improved more quickly than that of CT teams. During the exercise, the CT group did not achieve the level of performance of the control teams. The immediate effect of team member reconfiguration was to degrade performance significantly for the non-CT teams, but not for CT teams. The findings are discussed in terms of the multiple mental models' view of team performance (Cannon-Bowers et al. 1993) and the authors discuss the relative utility of cross-training when overall training time is fixed.     

Testing the effectiveness of icons for supporting distributed team decision making under time pressure

There has been minimal experimentation testing the effectiveness of icons (or interface features in general) on distributed team decision making. To overcome this deficiency, an experiment tested the effectiveness of a "send" icon to remind team members to send information to their teammates, and a "receive" icon to tell them when they had received information, for a simulated, military task. As predicted, the "send" icon was effective in maintaining information flow, particularly when time pressure was high and simulated teammates sent less information, because it reduced memory burden and supported proactive behavior. The "receive" icon was only effective in supporting decision accuracy when time pressure was low. As time pressure increased, participants' with the "receive" icon increasingly used a strategy of making decisions before reading the most important information, completely counter to expectations. These results illustrate the subtle, sometimes surprising way task characteristics (e.g., time pressure) can affect participants' strategies and, thereby, ify the positive effect of displays on performance. The experiment also examined other task characteristics and working memory capacity, and showed how the lens model equation (LME) helped explain all effects on decision accuracy.     

Heuristics for the time dependent team orienteering problem: Application to tourist route planning

The Time Dependent Team Orienteering Problem with Time Windows (TDTOPTW) can be used to model several real life problems. Among them, the route planning problem for tourists interested in visiting multiple points of interest (POIs) using public transportation. The main objective of this problem is to select POIs that match tourist preferences, taking into account a multitude of parameters and constraints while respecting the time available for sightseeing in a daily basis and integrating public transportation to travel between POIs (Tourist Trip Design Problem, TTDP). TDTOPTW is NP-hard while almost the whole body of the related literature addresses the non-time dependent version of the problem. The only TDTOPTW heuristic proposed so far is based on the assumption of periodic transit service schedules. Herein, we propose efficient cluster-based heuristics for the TDTOPTW which yield high quality solutions, take into account time dependency in calculating travel times between POIs and make no assumption on periodic service schedules. The validation scenario for our prototyped algorithms involved the transit network and real POI datasets compiled from the metropolitan area of Athens (Greece). Our TTDP algorithms handle arbitrary (i.e. determined at query time) rather than fixed start/end locations for derived tourist itineraries.     

Fuzzy decision making model for selection of real time location systems

Real Time Location Systems (RTLS) have gained importance in contemporary world since they allow real time positioning of assets, people and workflows. They can be used in different sectors to increase work efficiency and quality in areas of application. The selection of the appropriate RTLS technology becomes a major decision problem since it has a multi-criteria structure which includes both qualitative and quantitative factors. In this study, a decision making model is developed for selection of the appropriate RTLS technology for companies operating in different sectors. Three main criteria are determined by existing literature and with the help of the experts, namely economic, technical and implementation factors. The Fuzzy Analytic Hierarchy Process (FAHP) method is proposed to select the appropriate RTLS technology. Also sensitivity analysis is performed according to the incremental rates of main criteria. The model is applied to a hospital in Turkey considering three types of RTLS systems which are given as IR–RF hybrid, UHF RFID and Active RFID. Since the scores of the hybrid system for economic, implementation and technical factors are higher comparing the other technologies, it is selected as the best alternative.     

Two-level particle swarm optimization for the multi-modal team orienteering problem with time windows

This study presents a new variant of the team orienteering problem with time windows (TOPTW), called the multi-modal team orienteering problem with time windows (MM-TOPTW). The problem is motivated by the development of a tourist trip design application when there are several transportation modes available for tourists to choose during their trip. We develop a mixed integer programming model for MM-TOPTW based on the standard TOPTW model with additional considerations of transportation mode choices, including transportation cost and transportation time. Because MM-TOPTW is NP-hard, we design a two-level particle swarm optimization with multiple social learning terms (2L-GLNPSO) to solve the problem. To demonstrate the applicability and effectiveness of the proposed model and algorithm, we employ the proposed 2L-GLNPSO to solve 56 MM-TOPTW instances that are generated based on VRPTW benchmark instances. The computational results demonstrate that the proposed 2L-GLNPSO can obtain optimal solutions to small and medium-scale instances. For large-scale instances, 2L-GLNPSO is capable of producing high-quality solutions. Moreover, we test the proposed algorithm on standard TOPTW benchmark instances and obtains competitive results with the state-of-art algorithms.     

Measurements of team workload: A time pressure and scenario complexity study for maritime operation tasks

Workload is a critical factor influencing team performance in complex systems. There remains no consensus on the selection of team workload measures. Through an experiment based on simulated maritime operation tasks, team workload was manipulated by time pressure and scenario complexity to investigate the responses of three categories (subjective, performance-based, and physiological) of potential team workload measurements. The results show that time pressure had significant effects on all the three categories of measurements, especially on subjective indicators, miss rate, completion rate, operation accuracy, and eye movements. Significant main effects of scenario complexity on subjective team workload and the selected team performance measurements were also found, such as response latent time, miss rate, completion rate, and operation accuracy. Physiological measurements may not be sensitive for measuring team workload when scenario complexity serves as a major influencing factor of team workload.     

On the methods of decision making under uncertainty with probability information

By considering the decision maker's attitude of profit and risk, we propose an alternative selection method that can include the methods of decision making under ignorance and decision making under risk as special cases. An index to measure the decision maker's risk‐averse degree is proposed. With a given optimistic level of profit and risk, the evaluation results of the alternatives can be obtained with a geometric ordered weighted average (OWA) operator and a basic defuzzification distribution (BADD) neat OWA operator. Some properties of these two kinds of OWA operator in the problem of decision making under uncertainty are also proposed. © 2004 Wiley Periodicals, Inc. Int J Int Syst 19: 1217–1238, 2004.     

Supporting decision making and action selection under time pressure and uncertainty: the case of in-flight icing

Operators in high-risk domains such as aviation often need to make decisions under time pressure and uncertainty. One way to support them in this task is through the introduction of decision support systems (DSSs). The present study examined the effectiveness of two different DSS implementations: status and command displays. Twenty-seven pilots (9 pilots each in a baseline, status, and command group) flew 20 simulated approaches involving icing encounters. Accuracy of the decision aid (a smart icing system), familiarity with the icing condition, timing of icing onset, and autopilot usage were varied within subjects. Accurate information from either decision aid led to improved handling of the icing encounter. However, when inaccurate information was presented, performance dropped below that of the baseline condition. The cost of inaccurate information was particularly high for command displays and in the case of unfamiliar icing conditions. Our findings suggest that unless perfect reliability of a decision aid can be assumed, status displays may be preferable to command displays in high-risk domains (e.g., space flight, medicine, and process control), as the former yield more robust performance benefits and appear less vulnerable to automation biases.     

On the use of variograms for the prediction of time series

We consider the prediction of stationary stochastic processes with non-zero mean. When the covariance of the process is known, but the mean is not, the classical approach is to first estimate the mean from the past data, and then apply an optimal predictor to the zero-mean residuals. Bastin and Henriet [1] showed that an alternative was to use a predictor based on ‘variograms’ rather than covariance information, thus avoiding the estimation of the mean. We show here that the two predictors are identical when the unknown mean is replaced by its minimum variance estimate. We also examine, through simulation, how the two predictors compare when the statistics are unknown.     

On the valuation of alternatives for decision‐making under uncertainty

We focus on the problem of decision‐making in the face of uncertainty. The issue of the representation of uncertain information is considered and a number of different frameworks are described: possibilistic, probabilistic, belief structures, and graded possibilistic. We suggest methodologies for decision‐making in these different environments. The importance of decision attitude in the construction of decision functions is strongly emphasized. © 2002 Wiley Periodicals, Inc.     

On the evaluation of stress intensity factors for a simple crack under parametric loading

Two analytical approaches for the evaluation of stress intensity factors at the tips of a single straight crack in plane isotropic elasticity under symmetric tensile loading along the crack edges including a parameter are considered. The first method leads to an ordinary differential equation for the stress intensity factor (or to a system of such equations) with respect to the loading parameter, whereas the second method leads to closed-form results for the related integral by using Laplace transform techniques. Several elementary transcendental functions, such as the exponential function, were used in the loading distribution for an illustration of the present approaches and related results are presented. The computer algebra system Maple V was also used together with Gröbner bases (for the derivation of the differential equations) and with definite integration (for the derivation of the closed-form formulae).