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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. IP-based truck schedules for . assessment of the robustness of .
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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 isfunded by
IP-based truck schedules for Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013 assessment of the robustness of Simulation-based assessment of the robustness of IP-based truck schedules for cross-docking operations Simulation-based cross-docking operations Cross-dockingoperations IP-based truck schedule Robustnessassessment Results Conclusion - Cross-dockingoperations IP-based truck schedule Robustnessassessment Results Conclusion -
Anne-Laure Ladier, Allen Greenwood, GülgünAlpan, Halston Hales | EURO-INFORMS 2013 Cross-docking Lessthan 24h of temporary storage docking unloading Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion scanning transfer loading departing
Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013 Schedulingproblem • Minimize • Quantity put in storage • Dissatisfaction of the transport providers • Reservation system: 6am-9am 10am-12am 6am-9am 6am-8am 11am-12am Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion 9am-12am 7am-10am 6am-7am
Anne-Laure Ladier, Allen Greenwood, GülgünAlpan, Halston Hales | EURO-INFORMS 2013 IP model (IESM 2013, Rabat) • 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 unitsmovingfrom point to point (incl. storage) • Time windows for the trucks Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion
Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013 Research question How do randomeventsdistort the schedule ? How to assessitsrobustness? Whatshouldbechanged in the IP model to make the schedule more robust? Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion
Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013 Methodology • Discreteevents simulation • Simulatecomplexstochasticprocesses • Addlogic to react in unplanned situations • Gather data over multiple runs • Software: FlexSim (http://www.flexsim.com) Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion
Simulation and optimization Optimizationmodel Simulationmodel Simulationmodel Optimizationmodel Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion Optimizationmodel Optimizationmodel Simulationmodel Simulationmodel Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013
Principle Randomevents Simulationmodel Logic Optimizationmodel Truck schedule Logic Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion • Comparison • Truck arrival and departure time • Amount in storage • Pallettransfer Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013
Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013 Model demonstration
Anne-Laure Ladier, Allen Greenwood, GülgünAlpan, Halston Hales | EURO-INFORMS 2013 Validity range • Someassumptions are ratherstrong Are theyreasonable? • Internal operations are done in masked time, within one time unit Simulationmodel Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion Optimizationmodel
Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013 Insights from the simulation • Correlationbetweenerror in docking time and error in stay time? Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion All delayed trucks are critical No truck iscritical Somedelayed trucks are critical door1 door2 door3 Number of critical trucks a priori ≤ Nb of actualcritical trucks
Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013 Robustness • EverythingisdeterministicWhat if randomeventsoccur? • Trucks arrival time (early / late) Simulationmodel Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion Optimizationmodel
Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013 Robustness • EverythingisdeterministicWhat if randomeventsoccur? • Content of the inbound trucks Simulationmodel Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion Optimizationmodel
Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013 Conclusion • Simulation isused to assess the robustness, but also to gatherideas on robustnessimprovement • Ideas to make the IP model more robust • Add a flexible « buffer » door • Change the model to use n-1 doors • Avoidcritical trucks Cross-docking operations IP-based truck schedule Robustness assessment Results Conclusion
Thankyou for your attention! Questions? Contact: Anne-Laure.Ladier@g-scop.fr
Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013 IP* • Data • Decision variables
Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013 IP*
Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013
Anne-Laure Ladier, Allen Greenwood, Gülgün Alpan, Halston Hales | EURO-INFORMS 2013 Palletstransfer