| dc.description.abstract | Historically, the supply chain's echelons, such as warehouses, distributors, and
retailers, were managed independently, buffered by large inventories. Increasing
competitive pressures and market globalization are forcing firms to develop supply
chains that can respond quickly to customer needs; therefore, using multi-location,
multi-product inventory management interactively is recommended in assisting
companies in reducing operating costs and improving customer service. The current
paper analyses and evaluates the problem in the distribution system of a specific
company - DAI PHAT with the aim to propose a collaborative multi-echelon lighting
product supply chain composed of a central distribution center, multi-regional
warehouses, and multi-retailers using a stochastic multi-period and multi-product
mathematical model for the minimization of the total operating cost (simply expressed
in 2 types of cost: inventory management costs, and ordering cost).
The Greedy Heuristics is used to find out the solution of the problem built from a
mix-integer linear program model, which is run by Python software. The yielded
results help to define the location of the new warehouse, whether to order, the quantity
of the order, optimal safety stock, and inventory at each level corresponding to each
Regional Warehouse if needed for total cost reduction. Ultimately, to highlight the
credibility of the results from this research, Google Sheet implementation was applied.
Moreover, an execution of the CPLEX program is also applied to check the validity of
the Greedy Heuristics for this case. By conducting a sensitivity analysis, it is
discovered that certain parameters including inventory-holding cost and lead time are
considered to be the significant data as they have the most influence towards the
optimal result while ordering costs are seen to be a lesser influence on the ending total
cost. | en_US |
