Reverse Logistics Network Design Using a Hybrid Genetic Algorithm and Simulated Annealing Methodology

TUZKAYA, GÜLFEM; GÜLSÜN, Bahadır; Bildik, Ender

doi:10.4018/978-1-60566-808-6.ch007

Reverse Logistics Network Design Using a Hybrid Genetic Algorithm and Simulated Annealing Methodology

ELECTRONIC SUPPLY NETWORK COORDINATION IN INTELLIGENT AND DYNAMIC ENVIRONMENTS: MODELING AND IMPLEMENTATION, ss.168-186, 2011 (SCI-Expanded)

Yayın Türü: Makale / Tam Makale
Basım Tarihi: 2011
Doi Numarası: 10.4018/978-1-60566-808-6.ch007
Dergi Adı: ELECTRONIC SUPPLY NETWORK COORDINATION IN INTELLIGENT AND DYNAMIC ENVIRONMENTS: MODELING AND IMPLEMENTATION
Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED)
Sayfa Sayıları: ss.168-186
Yıldız Teknik Üniversitesi Adresli: Evet

Özet

Reverse logistics network design (RLND) effectiveness has an important impact on the effectiveness of the whole supply network coordination. Considering that, in this study, the RLND problem is investigated and a hybrid genetic algorithms and simulated annealing (HGASA) methodology is proposed. This problem is applied to a preceding study which utilized genetic algorithms (GA) for the optimization. HGASA and GA results are tested with Wilcoxon rank-sum test for hundred runs and the results prove the difference between two approaches. Additionally, the averages and the standard deviations support that, the HGASA algorithm increases the probability of obtaining better solutions.