Centre National de la Recherche Scientifique Institut National Polytechnique de Grenoble Université Joseph Fourier Laboratoire G-SCOP 46, av Félix Viallet Grenoble Cedex Simulation-based assessment of the robustness of IP-based truck schedules for cross-docking operations Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales This exchange program is funded by
Simulation-based assessment of the robustness of IP-based truck schedules for cross-docking operations IP-based truck schedules for cross-docking operations assessment of the robustness of Simulation-based Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion - Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion - 2 Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013
Cross-docking 3 Less than 24h of temporary storage docking unloading scanning transfer loading departing Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013 Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion
Scheduling problem 4 10am-12am 6am-8am 9am-12am 6am-7am 6am-9am 11am-12am 7am-10am Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013 Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion Minimize Quantity put in storage Dissatisfaction of the transport providers Reservation system:
IP model (IESM 2013, Rabat) min (penalty on the time window chosen + # pallets put in storage) Flow conservation (for each destination) # trucks present <= # doorsOutbound trucks leave when fully loadedTransfer capacity Assumptions Internal operations are done in masked time, within one time unit The door-to-door distance for the transfer is not taken into account The pallets unloaded on the floor can be picked in any order Decision variables # of units moving from point to point (incl. storage) Time windows for the trucks 5 Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013 Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion
Research question How do random events distort the schedule ? How to assess its robustness? What should be changed in the IP model to make the schedule more robust? Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion
Methodology Discrete events simulation Simulate complex stochastic processes Add logic to react in unplanned situations Gather data over multiple runs Software: FlexSim ( Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion
Simulation and optimization Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS Simulation model Optimization model Simulation model Optimization model Simulation model Optimization model Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion
Principle Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013 Simulation model Optimization model Truck schedule Truck arrival and departure time Amount in storage Pallet transfer Comparison Logic Random events 9 Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion
Model demonstration Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS
Validity range Some assumptions are rather strong Are they reasonable? Internal operations are done in masked time, within one time unit Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013 Simulation model Optimization model 11 Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion
door1 door2 door3 Insights from the simulation Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS Correlation between error in docking time and error in stay time? 0 Trucks stay longer than expected Docking times not affected between 0 and 1 Trucks stay longer than expected Docking time shifted 1 Trucks stay longer than expected Docking times shifted accordingly All delayed trucks are critical No truck is critical Some delayed trucks are critical Number of critical trucks a priori ≤ Nb of actual critical trucks Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion
Robustness Everything is deterministic What if random events occur? Trucks arrival time (early / late) Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013 Simulation model Optimization model 13 Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion
Robustness Everything is deterministic What if random events occur? Content of the inbound trucks Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013 Simulation model Optimization model 14 Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion
Simulation is used to assess the robustness, but also to gather ideas on robustness improvement Ideas to make the IP model more robust Add a flexible « buffer » door Change the model to use n-1 doors Avoid critical trucks Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion
Centre National de la Recherche Scientifique Institut National Polytechnique de Grenoble Université Joseph Fourier Laboratoire G-SCOP 46, av Félix Viallet Grenoble Cedex Thank you for your attention! Questions? Contact:
IP* Data Decision variables 17 Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013
IP* 18 Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013
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Pallets transfer Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS