Domain reduction using GRASP construction phase for transmission expansion planning problem


Autoria(s): Rahmani, Mohsen; Romero, Ruben A.; Rider, Marcos J.; Paredes, Miguel
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

27/05/2014

27/05/2014

03/04/2012

Resumo

This paper proposes a new strategy to reduce the combinatorial search space of a mixed integer linear programming (MILP) problem. The construction phase of greedy randomized adaptive search procedure (GRASP-CP) is employed to reduce the domain of the integer variables of the transportation model of the transmission expansion planning (TM-TEP) problem. This problem is a MILP and very difficult to solve specially for large scale systems. The branch and bound (BB) algorithm is used to solve the problem in both full and the reduced search space. The proposed method might be useful to reduce the search space of those kinds of MILP problems that a fast heuristic algorithm is available for finding local optimal solutions. The obtained results using some real test systems show the efficiency of the proposed method. © 2012 Springer-Verlag.

Formato

87-98

Identificador

http://dx.doi.org/10.1007/978-3-642-29124-1_8

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 7245 LNCS, p. 87-98.

0302-9743

1611-3349

http://hdl.handle.net/11449/73280

10.1007/978-3-642-29124-1_8

2-s2.0-84859150018

Idioma(s)

eng

Relação

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Direitos

closedAccess

Palavras-Chave #GRASP-CP #MILP #TM-TEP #Branch and bounds #Combinatorial search #Construction phase #Fast heuristic algorithms #Greedy randomized adaptive search procedure #Integer variables #Local optimal solution #Mixed-integer linear programming #Search spaces #Test systems #Transmission expansion planning #Transportation model #Combinatorial optimization #Heuristic algorithms #Linear programming #Problem solving
Tipo

info:eu-repo/semantics/conferencePaper