| dc.description.abstract | This essay focuses on setting up a closed loop supply chain for a battery manufacturer. Based on
[1], combining this forward and reverse supply chain is the primary purpose of solving problems
related to returned products. The main aim is to reduce costs to maximize profits. This
optimization model belongs to the Mixed-integer nonlinear programming (MINLP) problem so
that the two stages of resolution are set. First, MATLAB is the tool for solving the relaxation
nonlinear programming (NLP) problem. Second, the Mixed-integer programming (MIP) problem
is determined by the branch and bound method.
The results are entirely satisfactory, the profit margin from the closed loop supply chain is
significantly higher than the traditional supply chain. However, the data is the only relative, so
the results are not entirely correct. But it can be applied in practice if you study the market and
related fields thoroughly.
Keywords: Case study, Product life cycle, Mathematical programming, Mixed-integer nonlinear
programming, MATLAB. | en_US |
