Book Chapter

·2011

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

Gülfem Tuzkaya YTU , Bahadır Gülsün YTU , Ender Bildik YTU

IGI Global eBooks

Abstract

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.Request access from your librarian to read this chapter's full text.

Keywords

Simulated annealing Wilcoxon signed-rank test Genetic algorithm Computer science Algorithm Adaptive simulated annealing Mathematical optimization Machine learning Mathematics Statistics Mann–Whitney U test

Subject Areas

Quality and Supply Management ·Management Information Systems ·Social Sciences
Sustainable Supply Chain Management ·Strategy and Management ·Social Sciences
Digital Transformation in Industry ·Industrial and Manufacturing Engineering ·Physical Sciences