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Arsalan Rahmani

Arsalan Rahmani

Academic rank: Assistant Professor
ORCID:
Education: PhD.
ScopusId: 55881268200
Faculty: Faculty of Science
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Research

Title
Lagrangean relaxation-based algorithm for bi-level problems
Type
JournalPaper
Keywords
mixed-integer bi-level programming; Lagrangean relaxation; sub-gradient method; competitive bi-level capacitated facility location problem
Year
2015
Journal OPTIMIZATION METHODS & SOFTWARE
DOI
Researchers Arsalan Rahmani ، seyed ali mirhassani

Abstract

Under study is a special class of mixed-integer bi-level programming problem (BLPP) which arises in several areas such as engineering, transportation and control systems. The main characteristic of BLPP is that the outer optimization (upper level) problem is constrained by an inner optimization (lower level) problem. In this paper, a Lagrangean relaxation method is proposed to obtain an acceptable feasible solution by solving a sequence of one-level mixed-integer problems. The computational results on some examples were taken from literatures and randomly generated problems indicate that the method is able to solve the BLPP efficiently.