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DTSTAMP:20260410T180117
DTSTART:20170601T104500
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URL:http://murmitoyen.com/events/vanille/detail/767675
LOCATION:Université de Montréal - Pavillon André-Aisenstadt\, 2920\, che
 min de la Tour\, Montréal\, QC\, Canada\, H3T 1N8
SUMMARY:Séminaire du GERAD :  The pickup and delivery problem with LIFO co
 nstraints
DESCRIPTION:Titre : The pickup and delivery problem with LIFO constraints
\
 nConférencière : Marilène Cherkesly – Professeure\, Département de m
 anagement et technologie\, Université du Québec à Montréal\, Canada 
\
 nIn this presentation\, we propose models and algorithms for two variants 
 of the pickup and delivery problem with handling constraints: the pickup a
 nd delivery problem with time windows and last-in-first-out (LIFO) loading
  constraints (PDPTWL) and the pickup and delivery problem with time window
 s and multiple stacks (PDPTWMS). In the pickup and delivery problem\, vehi
 cles based at a depot are used to satisfy a set of requests which consists
  of transporting goods (or items) from a specific pickup location to a spe
 cific delivery location. We consider an unlimited fleet of identical vehic
 les with multiple homogeneous compartments of limited capacity. A vehicle 
 route is feasible if the load in each compartment of the vehicle does not 
 exceed its capacity and each completed request is first picked up at its p
 ickup location and then delivered at its corresponding delivery location. 
 In the PDPTWL\, the LIFO loading rule ensures that no handling is required
  prior to unloading an item from a vehicle: an item can only be delivered 
 if it is the last one in the stack. In the PDPTWMS\, each vehicle contains
  multiple stacks that are operated in a LIFO fashion. The problem consists
  of determining a set of least-cost feasible routes in which the number of
  vehicles is first minimized. To solve those variants of the pickup and de
 livery problem\, two families of branch-price-and-cut algorithms are devel
 oped. The first family tackles the handling constraints in the shortest pa
 th pricing problem and applies a dynamic programming algorithm relying on 
 an ad hoc dominance criterion. The second family incorporates the handling
  constraints partly in the shortest path pricing problem and adds addition
 al inequalities to the master problem when infeasible paths are encountere
 d. Known valid inequalities are adapted to the PDPTWL\, and the PDPTWMS. I
 nstances with up to 75 requests are solved within two hours of computation
 al time.
\nEntrée gratuite. Bienvenue à tous!
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