Big Bang-Big Crunch Optimization Algorithm for Solving the Uncapacitated Facility Location Problem

Yıl 2016, Cilt: 4 Sayı: Special Issue-1, 185 - 189, 26.12.2016

Ismail Koc

Öz

The
big bang–big crunch (BB–BC) algorithm has been proposed as a new optimization
method based on the big bang and big crunch theory, one of the theories of the
evolution of the universe. The BB-BC algorithm has been firstly presented to
solve the optimization problems with continuous solutions space. If the
solution space of the problem is binary-structural, the algorithm must be
modified to solve this kind of the problems. Therefore, in this study, the
BB-BC method, one of the population-based optimization algorithms, is modified
to deal with binary optimization problems. The performance of the proposed
methods is analyzed on uncapacitated facility location problems (UFLPs) which
are one of the binary problems used in literature. The well-known small and medium
twelve instances of UFLPs are used to analyze the performances and the effects
of the control parameter of the BB-BC algorithm. The obtained results are
comparatively presented. According to the experimental results, the binary
version of the BB-BC method achieves successful results in solving UFLP in
terms of solution quality.

Anahtar Kelimeler

Big Bang-Big Crunch Algorithm, Population-based optimization algorithms, Binary optimization, UFLP

Kaynakça

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