  Recent developments in urbanization and e-commerce have pushed businesses to
deploy efficient systems to decrease their supply chain cost. Vendor Managed
Inventory (VMI) is one of the most widely used strategies to effectively manage
supply chains with multiple parties. VMI implementation asks for solving the
Inventory Routing Problem (IRP). This study considers a multi-product
multi-period inventory routing problem, including a supplier, set of customers,
and a fleet of heterogeneous vehicles. Due to the complex nature of the IRP, we
developed a Modified Adaptive Genetic Algorithm (MAGA) to solve a variety of
instances efficiently. As a benchmark, we considered the results obtained by
Cplex software and an efficient heuristic from the literature. Through
extensive computational experiments on a set of randomly generated instances,
and using different metrics, we show that our approach distinctly outperforms
the other two methods.
