liu.seSearch for publications in DiVA

References$(function(){PrimeFaces.cw("TieredMenu","widget_formSmash_upper_j_idt152",{id:"formSmash:upper:j_idt152",widgetVar:"widget_formSmash_upper_j_idt152",autoDisplay:true,overlay:true,my:"left top",at:"left bottom",trigger:"formSmash:upper:referencesLink",triggerEvent:"click"});}); $(function(){PrimeFaces.cw("OverlayPanel","widget_formSmash_upper_j_idt153_j_idt155",{id:"formSmash:upper:j_idt153:j_idt155",widgetVar:"widget_formSmash_upper_j_idt153_j_idt155",target:"formSmash:upper:j_idt153:permLink",showEffect:"blind",hideEffect:"fade",my:"right top",at:"right bottom",showCloseIcon:true});});

Efficient Updating Shortest Path Calculations for Traffic AssignmentPrimeFaces.cw("AccordionPanel","widget_formSmash_some",{id:"formSmash:some",widgetVar:"widget_formSmash_some",multiple:true}); PrimeFaces.cw("AccordionPanel","widget_formSmash_all",{id:"formSmash:all",widgetVar:"widget_formSmash_all",multiple:true});
function selectAll()
{
var panelSome = $(PrimeFaces.escapeClientId("formSmash:some"));
var panelAll = $(PrimeFaces.escapeClientId("formSmash:all"));
panelAll.toggle();
toggleList(panelSome.get(0).childNodes, panelAll);
toggleList(panelAll.get(0).childNodes, panelAll);
}
/*Toggling the list of authorPanel nodes according to the toggling of the closeable second panel */
function toggleList(childList, panel)
{
var panelWasOpen = (panel.get(0).style.display == 'none');
// console.log('panel was open ' + panelWasOpen);
for (var c = 0; c < childList.length; c++) {
if (childList[c].classList.contains('authorPanel')) {
clickNode(panelWasOpen, childList[c]);
}
}
}
/*nodes have styleClass ui-corner-top if they are expanded and ui-corner-all if they are collapsed */
function clickNode(collapse, child)
{
if (collapse && child.classList.contains('ui-corner-top')) {
// console.log('collapse');
child.click();
}
if (!collapse && child.classList.contains('ui-corner-all')) {
// console.log('expand');
child.click();
}
}
PrimeFaces.cw("AccordionPanel","widget_formSmash_responsibleOrgs",{id:"formSmash:responsibleOrgs",widgetVar:"widget_formSmash_responsibleOrgs",multiple:true}); 2004 (English)Independent thesis Basic level (professional degree)Student thesis
##### Abstract [en]

##### Place, publisher, year, edition, pages

Matematiska institutionen , 2004.
##### Keyword [en]

Mathematical optimization, systems theory, Traffic Assignment, Frank-Wolfe Method, Shortest Path Problem, Network Simplex, Bucket Pricing, Conjugate Search Directions
##### Keyword [sv]

Optimeringslära, systemteori
##### National Category

Computational Mathematics
##### Identifiers

URN: urn:nbn:se:liu:diva-2573ISRN: LITH-MAT-EX--04/13--SEOAI: oai:DiVA.org:liu-2573DiVA: diva2:19908
##### Uppsok

fysik/kemi/matematik

#####

PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt400",{id:"formSmash:j_idt400",widgetVar:"widget_formSmash_j_idt400",multiple:true});
#####

PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt406",{id:"formSmash:j_idt406",widgetVar:"widget_formSmash_j_idt406",multiple:true});
#####

PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt413",{id:"formSmash:j_idt413",widgetVar:"widget_formSmash_j_idt413",multiple:true});
Available from: 2004-11-05 Created: 2004-11-05

Traffic planning in a modern congested society is an important and time consuming procedure. Finding fast algorithms for solving traffic problems is therefore of great interest for traffic planners allover the world.

This thesis concerns solving the fixed demand traffic assignment problem (TAP) on a number of different transportation test networks. TAP is solved using the Frank-Wolfe algorithm and the shortest path problems that arise as subproblems to the Frank-Wolfe algorithm are solved using the network simplex algorithm. We evaluate how a number of existing pricing strategies to the network simplex algorithm performs with TAP. We also construct a new efficient pricing strategy, the Bucket Pricing Strategy, inspired by the heap implementation of Dijkstra's method for shortest path problems. This pricing strategy is, together with the actual use of the network simplex algorithm, the main result of the thesis and the pricing strategy is designed to take advantage of the special structure of TAP. In addition to performing tests on the conventional Frank-Wolfe algorithm, we also test how the different pricing strategies perform on Frank-Wolfe algorithms using conjugate and bi-conjugate search directions.

These test results show that the updating shortest path calculations obtained by using the network simplex outperforms the non-updating Frank-Wolfe algorithms. Comparisons with Bar-Gera's OBA show that our implementation, especially together with the bucket pricing strategy, also outperforms this algorithm for relative gaps down to 10E-6.

References$(function(){PrimeFaces.cw("TieredMenu","widget_formSmash_lower_j_idt1144",{id:"formSmash:lower:j_idt1144",widgetVar:"widget_formSmash_lower_j_idt1144",autoDisplay:true,overlay:true,my:"left top",at:"left bottom",trigger:"formSmash:lower:referencesLink",triggerEvent:"click"});}); $(function(){PrimeFaces.cw("OverlayPanel","widget_formSmash_lower_j_idt1145_j_idt1147",{id:"formSmash:lower:j_idt1145:j_idt1147",widgetVar:"widget_formSmash_lower_j_idt1145_j_idt1147",target:"formSmash:lower:j_idt1145:permLink",showEffect:"blind",hideEffect:"fade",my:"right top",at:"right bottom",showCloseIcon:true});});