Sequential Optimization of Paths in Directed Graphs Relative to Different Cost Functions

Handle URI:
http://hdl.handle.net/10754/209371
Title:
Sequential Optimization of Paths in Directed Graphs Relative to Different Cost Functions
Authors:
Mahayni, Malek A.
Abstract:
Finding optimal paths in directed graphs is a wide area of research that has received much of attention in theoretical computer science due to its importance in many applications (e.g., computer networks and road maps). Many algorithms have been developed to solve the optimal paths problem with different kinds of graphs. An algorithm that solves the problem of paths’ optimization in directed graphs relative to different cost functions is described in [1]. It follows an approach extended from the dynamic programming approach as it solves the problem sequentially and works on directed graphs with positive weights and no loop edges. The aim of this thesis is to implement and evaluate that algorithm to find the optimal paths in directed graphs relative to two different cost functions ( , ). A possible interpretation of a directed graph is a network of roads so the weights for the function represent the length of roads, whereas the weights for the function represent a constraint of the width or weight of a vehicle. The optimization aim for those two functions is to minimize the cost relative to the function and maximize the constraint value associated with the function. This thesis also includes finding and proving the relation between the two different cost functions ( , ). When given a value of one function, we can find the best possible value for the other function. This relation is proven theoretically and also implemented and experimented using Matlab®[2].
Advisors:
Moshkov, Mikhail ( 0000-0003-0085-9483 )
Committee Member:
Alouini, Mohamed-Slim ( 0000-0003-4827-1793 ) ; Shihada, Basem ( 0000-0003-4434-4334 )
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Program:
Computer Science
Issue Date:
Jul-2011
Type:
Thesis
Appears in Collections:
Theses; Computer Science Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.advisorMoshkov, Mikhailen
dc.contributor.authorMahayni, Malek A.en
dc.date.accessioned2012-02-04T08:10:33Z-
dc.date.available2012-02-04T08:10:33Z-
dc.date.issued2011-07en
dc.identifier.urihttp://hdl.handle.net/10754/209371en
dc.description.abstractFinding optimal paths in directed graphs is a wide area of research that has received much of attention in theoretical computer science due to its importance in many applications (e.g., computer networks and road maps). Many algorithms have been developed to solve the optimal paths problem with different kinds of graphs. An algorithm that solves the problem of paths’ optimization in directed graphs relative to different cost functions is described in [1]. It follows an approach extended from the dynamic programming approach as it solves the problem sequentially and works on directed graphs with positive weights and no loop edges. The aim of this thesis is to implement and evaluate that algorithm to find the optimal paths in directed graphs relative to two different cost functions ( , ). A possible interpretation of a directed graph is a network of roads so the weights for the function represent the length of roads, whereas the weights for the function represent a constraint of the width or weight of a vehicle. The optimization aim for those two functions is to minimize the cost relative to the function and maximize the constraint value associated with the function. This thesis also includes finding and proving the relation between the two different cost functions ( , ). When given a value of one function, we can find the best possible value for the other function. This relation is proven theoretically and also implemented and experimented using Matlab®[2].en
dc.language.isoenen
dc.titleSequential Optimization of Paths in Directed Graphs Relative to Different Cost Functionsen
dc.typeThesisen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
thesis.degree.grantorKing Abdullah University of Science and Technologyen_GB
dc.contributor.committeememberAlouini, Mohamed-Slimen
dc.contributor.committeememberShihada, Basemen
thesis.degree.disciplineComputer Scienceen
thesis.degree.nameMaster of Scienceen
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