000746132 000__ 03304cam\a2200469Ii\4500
000746132 001__ 746132
000746132 005__ 20230306141237.0
000746132 006__ m\\\\\o\\d\\\\\\\\
000746132 007__ cr\cn\nnnunnun
000746132 008__ 150618s2015\\\\sz\a\\\\ob\\\\001\0\eng\d
000746132 020__ $$a9783319176659$$qelectronic book
000746132 020__ $$a331917665X$$qelectronic book
000746132 020__ $$z9783319176642
000746132 0247_ $$a10.1007/978-3-319-17665-9$$2doi
000746132 035__ $$aSP(OCoLC)ocn911179612
000746132 035__ $$aSP(OCoLC)911179612
000746132 040__ $$aN$T$$beng$$erda$$epn$$cN$T$$dN$T$$dGW5XE$$dCDX$$dIDEBK$$dYDXCP$$dEBLCP$$dUPM$$dVLB$$dOCLCF$$dCOO
000746132 049__ $$aISEA
000746132 050_4 $$aVK570$$b.T54 2015eb
000746132 08204 $$a623.89$$223
000746132 1001_ $$aTierney, Kevin,$$eauthor.
000746132 24510 $$aOptimizing liner shipping fleet repositioning plans$$h[electronic resource] /$$cKevin Tierney.
000746132 264_1 $$aCham :$$bSpringer,$$c2015.
000746132 300__ $$a1 online resource :$$billustrations.
000746132 336__ $$atext$$btxt$$2rdacontent
000746132 337__ $$acomputer$$bc$$2rdamedia
000746132 338__ $$aonline resource$$bcr$$2rdacarrier
000746132 4901_ $$aOperations research/computer science interfaces series ;$$vvolume 57
000746132 504__ $$aIncludes bibliographical references and index.
000746132 5050_ $$aIntroduction -- Containerized Shipping -- Liner Shipping Fleet Repositioning -- Methodological Background -- Liner Shipping Fleet Repositioning without Cargo -- Liner Shipping Fleet Repositioning with Cargo -- Conclusion.
000746132 506__ $$aAccess limited to authorized users.
000746132 520__ $$aThis 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.
000746132 588__ $$aOnline resource; title from PDF title page (viewed June 19, 2015).
000746132 650_0 $$aOptimum ship routing.
000746132 650_0 $$aElectronics in navigation.
000746132 650_0 $$aCargo ships.
000746132 77608 $$iPrint version:$$z9783319176642
000746132 830_0 $$aOperations research/computer science interfaces series ;$$vv. 57.
000746132 85280 $$bebk$$hSpringerLink
000746132 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-17665-9$$zOnline Access$$91397441.1
000746132 909CO $$ooai:library.usi.edu:746132$$pGLOBAL_SET
000746132 980__ $$aEBOOK
000746132 980__ $$aBIB
000746132 982__ $$aEbook
000746132 983__ $$aOnline
000746132 994__ $$a92$$bISE