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This paper describes the conceptual ideas behind a computer-aided microsimulation model combining agent-based modeling and discrete event simulation in order to reproduce the complex behavior of a fictitious subway system. Such a model allows passengers to be both active and passive agents behaving according to the model rules, and also affecting them in return, for more realistic results. Decision support in this network can be approached from both the passenger and the network operator perspective, by correctly predicting ridership and system delays. Preliminary results are presented, together with some of the challenges faced throughout the development process.

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The present paper discusses key aspects of managerial human factors in research, specifically when implementing decision support systems in the context of Humanitarian Logistics. It is framed as a follow-up of an Operations Research-based project developing a decision support framework for relief distribution in the event of a catastrophic blackout. Specifically, the main lessons learned from this project are explored to understand the role that experts and decision makers play when conducting research in the fast-growing area of Humanitarian Logistics.