Publications HAL de Halston,Hales

Communication dans un congrès

ref_biblio
Anne-Laure Ladier, Allen G. Greenwood, Gülgün Alpan, Halston Hales. Simulation-based assessment of the robustness of IP-based truck schedules for cross-docking operations. 26th European Conference on Operation Research, Jul 2013, Rome, Italy. ⟨hal-00859897⟩
resume
A previously developed IP-based model for scheduling truck arrivals, truck departures, and pallet handling in a cross-docking platform is assessed using discrete-event simulation. Experimentation with a simulation model of basic cross-docking operations subjects the schedules to a more realistic environment (e.g., stochastic truck arrival times, pallets transfer times, truck content) than can be formulated in the IP model. Analysis of the simulation experiments, in terms of the schedules' performance and robustness under pragmatic conditions, provides insights to help refine the IP model.
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ref_biblio
Allen G. Greenwood, Halston Hales, Gülgün Alpan, Anne-Laure Ladier. Performance evaluation of worker timetables in cross-docking facilities using simulation. 26th European Conference on Operation Research, Jul 2013, Rome, Italy. ⟨hal-00966688⟩
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Rapport

ref_biblio
Anne-Laure Ladier, Allen G. Greenwood, Gülgün Alpan, Halston Hales. Issues in the complementary use of simulation and optimization modeling. [Research Report] --. 2014. ⟨hal-00946541⟩
resume
Simulation models and discrete optimization models are oftentimes used together in a variety of ways. In this paper, we discuss the issues that modelers must address in cases where simulation models are used to test a discrete mathematical programming optimization model's performance in a stochastic environment. The issues arise during validation of simulation models, when checking agreement between deterministic optimization results and simulation models operating under deterministic conditions. In our case, the issues are derived from validating simulation models that are used to test the performance of scheduling and resource allocation models (integer and mixed-integer programming optimization models) under various types of uncertainty. While the concerns we describe are from our work in the logistics domain (cross-docking operations), they are relevant to a wide variety of problem domains. In addition to describing the issues, we offer suggestions on how modelers might address the concerns.
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