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Scheduling truck arrivals and departures in a cross-dock

Scheduling truck arrivals and departures in a cross-dock. Earliness, tardiness and storage policies. Anne-Laure Ladier , Gülgün Alpan International Conference on Industrial Engineering and Systems Management Oct 29, Rabat, Morocco. Outline. Cross-docking.

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Scheduling truck arrivals and departures in a cross-dock

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  1. Scheduling truck arrivals and departures in a cross-dock Earliness, tardiness and storage policies Anne-Laure Ladier, GülgünAlpan International Conference on Industrial Engineering and Systems Management Oct 29, Rabat, Morocco

  2. A.-L. Ladier, G. Alpan | IESM 2013 Outline

  3. A.-L. Ladier, G. Alpan | IESM 2013 Cross-docking Lessthan 24h of temporary storage Context Problem IP model Heuristics Conclusion

  4. A.-L. Ladier, G. Alpan | IESM 2013 Cross-docking • Key elements: • Synchronisation • Truck ponctuality[Boysen 2010][Boysen and Fliedner 2010] • Time windows • Wishedarrival and departure time (inbound) [Lim et al. 2005][Lim et al. 2006] • Ponctualityinboundandoutbound Context Problem IP model Heuristics Conclusion

  5. A.-L. Ladier, G. Alpan | IESM 2013 Assumptions • Platform • Exclusive door service mode (inbound or outbound) • Door-to-door distance for the transfer not taken into account • The storage capacity is unlimited • Trucks • Outbound trucks have a fixed capacity • Outbound trucks leave only when they are fully loaded • Internal operations • Internal operations are done in masked time (one time unit) • Unloaded pallets can be picked from the floor in any order • Matching truck not available => pallet goes into storage Context Problem IP model Heuristics Conclusion

  6. A.-L. Ladier, G. Alpan | IESM 2013 Schedulingproblem • Reservation system: 6am-9am 10am-12am 6am-9am 6am-8am 11am-12am 9am-12am 7am-10am 6am-7am Context Problem IP model Heuristics Conclusion

  7. A.-L. Ladier, G. Alpan | IESM 2013 Objective • Minimize • Quantity put in storage • Dissatisfaction of the transport providers Context Problem IP model Heuristics Conclusion

  8. A.-L. Ladier, G. Alpan | IESM 2013 Input data • Number of inbound and outbounddoors • Internalcapacity • Number of destinations • Number of inbound and outbound trucks • Destinations of the outbound trucks • Number of pallets per destination in eachinbound truck • Outbound trucks capacity • Possible presence slots per truck, and associated penalties ∞ 6am-9am 10am-12am 6am-9am 6am-8am C 11am-12am 9am-12am Context Problem IP model Heuristics Conclusion 7am-10am 6am-7am

  9. A.-L. Ladier, G. Alpan | IESM 2013 Decisions variables • # of unitsmovingateach time period: • fromeachinbound truck to eachoutbound truck • fromeachinbound truck to storage • fromstorage to eachoutbound truck • Time windowschosen for the trucks Context Problem IP model Heuristics Conclusion

  10. A.-L. Ladier, G. Alpan | IESM 2013 IP model (IP*) Context Problem IP model Heuristics Conclusion

  11. A.-L. Ladier, G. Alpan | IESM 2013 Computationallimits Context Problem IP model Heuristics Conclusion

  12. Heuristic 1 H1 Obj: minimize difference between inbound pallet supply and outbound pallet demand (synchronize inbound and outbound) Sameobjfunctionthan (IP*) Context Problem IP model Heuristics Conclusion A.-L. Ladier, G. Alpan | IESM 2013

  13. Heuristic 2 H2 Obj: minimize the outbound transport providers' dissatisfaction. Context Problem IP model Heuristics Conclusion Sameobjfunctionthan (IP*) A.-L. Ladier, G. Alpan | IESM 2013

  14. A.-L. Ladier, G. Alpan | IESM 2013 Results Context Problem IP model Heuristics Conclusion Gap to optimal: lessthan 6%

  15. A.-L. Ladier, G. Alpan | IESM 2013 Results (2) 4 inb / 4 outbdoors Context Problem IP model Heuristics Conclusion

  16. A.-L. Ladier, G. Alpan | IESM 2013 Followingwork • Make the solution more robust • How to evaluate the robustness? Joint use of optimisation and simulation [Ladier et al, EURO 2013][Ladier et al., Simulation workshop 2014][Ladier et al., ISERC 2014] • Testingdifferentrobustnessapproaches[work in progress] • Smooth the workload balance • Link with an employee scheduling module [Ladier et al, EJOR, to appear] Context Problem IP model Heuristics Conclusion

  17. A.-L. Ladier, G. Alpan | IESM 2013 Other perspectives • Refine the models • Distance or congestion • LIFO/FIFO loading and unloading • Flexible allocation of the doorrole (I/O) • Allow the trucks to leave non-full => effect on the inventory • Propose other solution approaches to deal withbiggerplatforms Context Problem IP model Heuristics Conclusion

  18. Thankyou for your attention! Questions? Anne-Laure.Ladier@grenoble-inp.fr www.g-scop.fr\~ladiera

  19. A.-L. Ladier, G. Alpan | IESM 2013 IP* • Data • Decision variables

  20. A.-L. Ladier, G. Alpan | IESM 2013 IP*

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