A modified adaptive genetic algorithm for multi-product multi-period inventory routing problem

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