| dc.description.abstract | This study proposes an innovative framework to simultaneously deal with the optimal
planning of the frozen product delivery and the optimal planning of daily route-to-market
of FMCG's enterprises, especially Unilever Vietnam. However, the outbreak and related
effects of the COVID-19 has led to assorted challenges and substantial disruption to the
Frozen product delivery. It is significant to prioritize identifying those challenges,
classify and put them as the input for resolving vehicle routing problems. Therefore, this
study has two phases including IFS – DEMATEL for discovering the key challenges and
a new Mixed Integer Linear Programming (MILP) for proposing optimal decisions
regarding the served customer’s quantities, required resources quantities and the daily
delivery plans of the supply chain network. The approach of IFS – DEMATEL
(Intuitionistic Fuzzy Sets – Decision – Making Trial and Evaluation Laboratory) dissects
and tackles the uncertainty of key challenges, points out the cause - effect
interrelationship among those challenges and the critical challenges. Besides, MILP has
been adopted to generate a model to totals costs, consisting of transportation cost and
wasted costs caused by damage cargoes. Finally, to evaluate the near – optimal solution
of the rental transportation cost and damaged product cost, the Nearest Greedy algorithm
is implemented. As a result, this study offers an efficient distribution network leading to
improving customers' satisfaction with better qualified products and reducing consumed
energy for traveling and cooling systems which contribute to sustainable goals of
enterprise. | en_US |
