Static pickup and delivery problems: a classification scheme and survey
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Cites background from "Static pickup and delivery problems..."
...For excellent recent reviews on dynamic pick-up-and-delivery problems see Berbeglia et al. (2010) and Cordeau et al. (2007). A transportation request for an urban taxi typically arrives only a short time before the desired departure (Lee et al., 2004) and vehicle routes and schedules are updated each time a new transportation request arrives. The dynamic ride-sharing environment resembles an urban taxi environment in terms of the arrival process of transportation requests, i.e., rides, but also has the added complexity of an arrival process of transportation resources, i.e., drivers. That is, a urban taxi system tends to have better information about where and when individual resources will become available. Note that it is often passenger convenience rather than physical capacity that keeps taxis from serving multiple passengers simultaneously. Horn (2002) demonstrate that allowing multiple passenger parties together in a single taxi trip may decrease system-wide vehicle miles but increase the individual travel times of the passengers. They present a dispatching software to manage a fleet of demand-responsive taxis taking into account both passenger service quality considerations and fleet efficiency considerations. The system assigns new travel requests to vehicles based on minimum cost criteria and then periodically applies improvement procedures. The author conducts a number of simulation studies based on data from a real-life taxi operator in Australia. The tests show that the software tool operates effectively in a fairly dynamic environment and realistic problems sizes. Dial (1995) proposes an autonomous dial-a-ride taxi service that shares many similarities with dynamic ride-sharing. The fully automated system lets passengers reserve trips by phone or computer on short-notice. For routing and dispatching, the author suggests the use of a dynamic programming approach of Psaraftis (1980). The dynamic algorithm reoptimizes the not yet executed part of the tentative optimal route each time a new request appears. Since the algorithm can only solve very small instances the system only includes passenger requests that want to be served in the near future and runs the algorithm for each vehicle individually. In the area of freight transportation, full truckload carriers have to manage fleets of vehicles (e.g. containers, trailers, boxcars) that serve one load at a time, with orders continuously arriving over time (for a review see Powell et al. (2007)). The problem of sequentially assigning transportation requests to vehicles is typically referred to as the dynamic assignment problem (Spivey and Powell, 2004) or the dynamic stacker crane problem (Berbeglia et al., 2010). Yang et al. (2004) consider the real-time multi-vehicle truckload pickup and delivery problem....
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...For excellent recent reviews on dynamic pick-up-and-delivery problems see Berbeglia et al. (2010) and Cordeau et al. (2007). A transportation request for an urban taxi typically arrives only a short time before the desired departure (Lee et al., 2004) and vehicle routes and schedules are updated each time a new transportation request arrives. The dynamic ride-sharing environment resembles an urban taxi environment in terms of the arrival process of transportation requests, i.e., rides, but also has the added complexity of an arrival process of transportation resources, i.e., drivers. That is, a urban taxi system tends to have better information about where and when individual resources will become available. Note that it is often passenger convenience rather than physical capacity that keeps taxis from serving multiple passengers simultaneously. Horn (2002) demonstrate that allowing multiple passenger parties together in a single taxi trip may decrease system-wide vehicle miles but increase the individual travel times of the passengers. They present a dispatching software to manage a fleet of demand-responsive taxis taking into account both passenger service quality considerations and fleet efficiency considerations. The system assigns new travel requests to vehicles based on minimum cost criteria and then periodically applies improvement procedures. The author conducts a number of simulation studies based on data from a real-life taxi operator in Australia. The tests show that the software tool operates effectively in a fairly dynamic environment and realistic problems sizes. Dial (1995) proposes an autonomous dial-a-ride taxi service that shares many similarities with dynamic ride-sharing. The fully automated system lets passengers reserve trips by phone or computer on short-notice. For routing and dispatching, the author suggests the use of a dynamic programming approach of Psaraftis (1980). The dynamic algorithm reoptimizes the not yet executed part of the tentative optimal route each time a new request appears....
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...For excellent recent reviews on dynamic pick-up-and-delivery problems see Berbeglia et al. (2010) and Cordeau et al. (2007). A transportation request for an urban taxi typically arrives only a short time before the desired departure (Lee et al....
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...For excellent recent reviews on dynamic pick-up-and-delivery problems see Berbeglia et al. (2010) and Cordeau et al. (2007). A transportation request for an urban taxi typically arrives only a short time before the desired departure (Lee et al., 2004) and vehicle routes and schedules are updated each time a new transportation request arrives. The dynamic ride-sharing environment resembles an urban taxi environment in terms of the arrival process of transportation requests, i.e., rides, but also has the added complexity of an arrival process of transportation resources, i.e., drivers. That is, a urban taxi system tends to have better information about where and when individual resources will become available. Note that it is often passenger convenience rather than physical capacity that keeps taxis from serving multiple passengers simultaneously. Horn (2002) demonstrate that allowing multiple passenger parties together in a single taxi trip may decrease system-wide vehicle miles but increase the individual travel times of the passengers....
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...For excellent recent reviews on dynamic pick-up-and-delivery problems see Berbeglia et al. (2010) and Cordeau et al. (2007). A transportation request for an urban taxi typically arrives only a short time before the desired departure (Lee et al., 2004) and vehicle routes and schedules are updated each time a new transportation request arrives. The dynamic ride-sharing environment resembles an urban taxi environment in terms of the arrival process of transportation requests, i.e., rides, but also has the added complexity of an arrival process of transportation resources, i.e., drivers. That is, a urban taxi system tends to have better information about where and when individual resources will become available. Note that it is often passenger convenience rather than physical capacity that keeps taxis from serving multiple passengers simultaneously. Horn (2002) demonstrate that allowing multiple passenger parties together in a single taxi trip may decrease system-wide vehicle miles but increase the individual travel times of the passengers. They present a dispatching software to manage a fleet of demand-responsive taxis taking into account both passenger service quality considerations and fleet efficiency considerations. The system assigns new travel requests to vehicles based on minimum cost criteria and then periodically applies improvement procedures. The author conducts a number of simulation studies based on data from a real-life taxi operator in Australia. The tests show that the software tool operates effectively in a fairly dynamic environment and realistic problems sizes. Dial (1995) proposes an autonomous dial-a-ride taxi service that shares many similarities with dynamic ride-sharing. The fully automated system lets passengers reserve trips by phone or computer on short-notice. For routing and dispatching, the author suggests the use of a dynamic programming approach of Psaraftis (1980). The dynamic algorithm reoptimizes the not yet executed part of the tentative optimal route each time a new request appears. Since the algorithm can only solve very small instances the system only includes passenger requests that want to be served in the near future and runs the algorithm for each vehicle individually. In the area of freight transportation, full truckload carriers have to manage fleets of vehicles (e.g. containers, trailers, boxcars) that serve one load at a time, with orders continuously arriving over time (for a review see Powell et al. (2007))....
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800 citations
703 citations
Cites background or methods from "Static pickup and delivery problems..."
...A survey on different solution methods can be found in (Berbeglia et al., 2007)....
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...Another survey on different solution methods can be found in Berbeglia et al. (2007)....
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638 citations
Cites background from "Static pickup and delivery problems..."
...These problems are the dynamic counterparts of the one-to-one static PDPs surveyed in Berbeglia et al. (2007)....
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...These problems are the dynamic counterparts of the one-to-one static PDPs surveyed in Berbeglia et al. (2007). Finally, some conclusions are provided in Section 7....
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References
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"Static pickup and delivery problems..." refers methods in this paper
...In the first phase clusters of customers are formed using the average linkage method ( Anderberg 1973 )....
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