Exact and approximate algorithms for the inventory routing problem
Exact and approximate algorithms for the inventory routing problem
In this thesis we develop exact and approximate algorithms for the inventory
routing problem (IRP). The inventory routing problem is one of deciding an
optimal delivery policy for a set of customers through a given planning period.
Customers can hold inventory and do not need deliveries every day. Deliveries
are carried out by a fleet of homogeneous vehicles that must be routed to travel a
minimum distance while visiting all customers scheduled for that day. Decisions
concern which customers to be visited and how much to deliver to each of them
must be taken.
A new formulation for the IRP is presented as a mixed integer programming
model. This new approach allows split deliveries so customers can receive the
inventory through more than one vehicle during the same day. It also seeks
periodic solutions through a given planning period. Although throughout our
research the planning period is fixed, all algorithms presented in this thesis can
be applied to any length of the planning period. Special cases for this problem
are also considered and optimal polynomial algorithms have been developed.
We develop four constructive heuristics for the inventory routing problem.
These heuristics are based on a schedule-first route-second approach. First, a
decision is made on which customers to visit each day, and how much inventory
they should receive on each delivery. Then, a vehicle routing problem is solved
for each day to perform the deliveries to the customers. Several experiments
are carried out to compare the performance of each heuristic. An iterated local
search method is then applied to the best solution obtained with these heuristics.
The local search is based on node interchange and aims to reduce the number of
routes per day as well as the total distance travelled. Extensive computational
tests are carried out to asses the effectiveness of this local search procedure.
Cabo Nodar, Marta
17fab2bf-37d3-42bf-acdc-20d5bf3d59d1
September 2003
Cabo Nodar, Marta
17fab2bf-37d3-42bf-acdc-20d5bf3d59d1
Cabo Nodar, Marta
(2003)
Exact and approximate algorithms for the inventory routing problem.
University of Southampton, School of Mathematics, Doctoral Thesis, 190pp.
Record type:
Thesis
(Doctoral)
Abstract
In this thesis we develop exact and approximate algorithms for the inventory
routing problem (IRP). The inventory routing problem is one of deciding an
optimal delivery policy for a set of customers through a given planning period.
Customers can hold inventory and do not need deliveries every day. Deliveries
are carried out by a fleet of homogeneous vehicles that must be routed to travel a
minimum distance while visiting all customers scheduled for that day. Decisions
concern which customers to be visited and how much to deliver to each of them
must be taken.
A new formulation for the IRP is presented as a mixed integer programming
model. This new approach allows split deliveries so customers can receive the
inventory through more than one vehicle during the same day. It also seeks
periodic solutions through a given planning period. Although throughout our
research the planning period is fixed, all algorithms presented in this thesis can
be applied to any length of the planning period. Special cases for this problem
are also considered and optimal polynomial algorithms have been developed.
We develop four constructive heuristics for the inventory routing problem.
These heuristics are based on a schedule-first route-second approach. First, a
decision is made on which customers to visit each day, and how much inventory
they should receive on each delivery. Then, a vehicle routing problem is solved
for each day to perform the deliveries to the customers. Several experiments
are carried out to compare the performance of each heuristic. An iterated local
search method is then applied to the best solution obtained with these heuristics.
The local search is based on node interchange and aims to reduce the number of
routes per day as well as the total distance travelled. Extensive computational
tests are carried out to asses the effectiveness of this local search procedure.
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Published date: September 2003
Organisations:
University of Southampton
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Local EPrints ID: 50599
URI: http://eprints.soton.ac.uk/id/eprint/50599
PURE UUID: 1cdb7b8f-c1ee-4bbd-afb3-5a1a033f2b0a
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Date deposited: 19 Mar 2008
Last modified: 13 Mar 2019 20:51
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Author:
Marta Cabo Nodar
University divisions
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