| dc.description.abstract | This thesis studies a multi - depot distribution system. In this system, the products must be
delivered from a group of depots to several retailers in a finite time horizon—the shipments
from the depots to retailers of the homogeneous vehicle with limited carrying capacity.
Customer demand at each retailer is dynamic with different periods. Decisions in this
system include replenishment quantities at each retailer during considered periods and its
corresponding delivery route with minimum total inventory and routing cost during the
considered time horizon. This thesis considers the problem as a Multi-Depot Inventory
Routing Problem (MDIRP). In general, the MDIRP is an NP-hard problem that optimizes
the trade-off between inventory and transportation management in an integrated way. A
Mixed-Integer Linear Programming model is formulated to solve it, and then this thesis
proposes a three-phase decomposition matheuristic to solve the problem in real-size
problem efficiently. In the first phase of the matheuristic, an integer program is solved to
build clusters, while the second phase generates routes. Finally, in the third phase, a routebased formulation of the problem is solved to obtain the final a feasible MDIRP solution.
More emphasis is devoted to simultaneously balancing several factors that impact the
clustering and route construction phases: distances, demand and inventory levels, time
horizon extension and vehicle capacity. Computational experiments show that the
matheuristic is very effective. | en_US |
