國立虎尾科技大學 |

Optimizing Liner Shipping Fleet Repositioning Plans

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Optimizing Liner Shipping Fleet Repositioning Plans/ by Kevin Tierney.
Author:	Tierney, Kevin.
Description:	VIII, 182 p. 49 illus., 20 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Operations research. -
Online resource:	https://doi.org/10.1007/978-3-319-17665-9
ISBN:	9783319176659

Optimizing Liner Shipping Fleet Repositioning Plans
Tierney, Kevin.

Optimizing Liner Shipping Fleet Repositioning Plans[electronic resource] /by Kevin Tierney. - 1st ed. 2015. - VIII, 182 p. 49 illus., 20 illus. in color.online resource. - Operations Research/Computer Science Interfaces Series,571387-666X ;. - Operations Research/Computer Science Interfaces Series,59.

Introduction -- Containerized Shipping -- Liner Shipping Fleet Repositioning -- Methodological Background -- Liner Shipping Fleet Repositioning without Cargo -- Liner Shipping Fleet Repositioning with Cargo -- Conclusion.

This monograph addresses several critical problems to the operations of shipping lines and ports, and provides algorithms and mathematical models for use by shipping lines and port authorities for decision support. One of these problems is the repositioning of container ships in a liner shipping network in order to adjust the network to seasonal shifts in demand or changes in the world economy. We provide the first problem description and mathematical model of repositioning and define the liner shipping fleet repositioning problem (LSFRP). The LSFRP is characterized by chains of interacting activities with a multi-commodity flow over paths defined by the activities chosen. We first model the problem without cargo flows with a variety of well-known optimization techniques, as well as using a novel method called linear temporal optimization planning that combines linear programming with partial-order planning in a branch-and-bound framework. We then model the LSFRP with cargo flows, using several different mathematical models as well as two heuristic approaches. We evaluate our techniques on a real-world dataset that includes a scenario from our industrial collaborator. We show that our approaches scale to the size of problems faced by industry, and are also able to improve the profit on the reference scenario by over US$14 million.

ISBN: 9783319176659

Standard No.: 10.1007/978-3-319-17665-9doiSubjects--Topical Terms:

573517
Operations research.

LC Class. No.: HD30.23

Dewey Class. No.: 658.40301

Optimizing Liner Shipping Fleet Repositioning Plans
LDR:03044nam a22004215i 4500 001 968076
003 DE-He213
005 20200919062800.0
007 cr nn 008mamaa
008 201211s2015 gw | s |||| 0|eng d
020 $a 9783319176659 $9 978-3-319-17665-9
024 7 $a 10.1007/978-3-319-17665-9 $2 doi
035 $a 978-3-319-17665-9
050 4 $a HD30.23
072 7 $a KJT $2 bicssc
072 7 $a BUS049000 $2 bisacsh
072 7 $a KJT $2 thema
072 7 $a KJMD $2 thema
082 0 4 $a 658.40301 $2 23
100 1 $a Tierney, Kevin. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1263736
245 1 0 $a Optimizing Liner Shipping Fleet Repositioning Plans $h [electronic resource] / $c by Kevin Tierney.
250 $a 1st ed. 2015.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2015.
300 $a VIII, 182 p. 49 illus., 20 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Operations Research/Computer Science Interfaces Series, $x 1387-666X ; $v 57
505 0 $a Introduction -- Containerized Shipping -- Liner Shipping Fleet Repositioning -- Methodological Background -- Liner Shipping Fleet Repositioning without Cargo -- Liner Shipping Fleet Repositioning with Cargo -- Conclusion.
520 $a This monograph addresses several critical problems to the operations of shipping lines and ports, and provides algorithms and mathematical models for use by shipping lines and port authorities for decision support. One of these problems is the repositioning of container ships in a liner shipping network in order to adjust the network to seasonal shifts in demand or changes in the world economy. We provide the first problem description and mathematical model of repositioning and define the liner shipping fleet repositioning problem (LSFRP). The LSFRP is characterized by chains of interacting activities with a multi-commodity flow over paths defined by the activities chosen. We first model the problem without cargo flows with a variety of well-known optimization techniques, as well as using a novel method called linear temporal optimization planning that combines linear programming with partial-order planning in a branch-and-bound framework. We then model the LSFRP with cargo flows, using several different mathematical models as well as two heuristic approaches. We evaluate our techniques on a real-world dataset that includes a scenario from our industrial collaborator. We show that our approaches scale to the size of problems faced by industry, and are also able to improve the profit on the reference scenario by over US$14 million.
650 0 $a Operations research. $3 573517
650 0 $a Decision making. $3 528319
650 0 $a Production management. $3 566447
650 0 $a International economics. $3 680327
650 1 4 $a Operations Research/Decision Theory. $3 669176
650 2 4 $a Operations Management. $3 1069063
650 2 4 $a International Economics. $3 669217
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319176666
776 0 8 $i Printed edition: $z 9783319176642
776 0 8 $i Printed edition: $z 9783319368412
830 0 $a Operations Research/Computer Science Interfaces Series, $x 1387-666X ; $v 59 $3 1255663
856 4 0 $u https://doi.org/10.1007/978-3-319-17665-9
912 $a ZDB-2-SBE
912 $a ZDB-2-SXBM
950 $a Business and Economics (SpringerNature-11643)
950 $a Business and Management (R0) (SpringerNature-43719)