| dc.description.abstract | In today’s modern world, inventory management has become an increasing concern for
companies and business leaders, especially the issue of limited space with certain
inventory stocks. Therefore, the Offsetting Inventory Cycle Problem (OICP) has been a
long-lasting matter of businesses, as the need of minimize warehouse space with a
reasonable replenishment plan has required consistent update and improvements in the
methodology. Regarding the case of Viet Dang Joint Stock Company, a leading business
in the dental industry, problems arises as goods are overstocked and kept for a long time,
which increases warehouse holding cost and takes up a considerable space in the
warehouse. This study examined the implementation of Mixed Integer Programming
(MIP) approach and metaheuristic algorithm, particularly Particle Swarm Optimization
(PSO), in order to enhance the efficiency of inventory management practices of Viet
Dang JSC. Data for validation was obtained from the original author’s paper. The case
study utilizes the real data from Viet Dang Joint Stock Company, where the need of
improving inventory management executions is urgent. The validation results indicate
that the proposed PSO model with is the best fit model for the available dataset, with
shorter time of execution and gives the closer results to the key paper. The numerical
results highlight that two approaches MIP and PSO both produce under 39,000 of space
occupied for goods, which significantly reduces the original space utilized, saving
inventory holding costs and leave space either for the development of office work or
improvement on new segment of goods. | en_US |
