Abstract
Vehicle Routing Problem (VRP) is a well-known challenging nondeterministic polynomial-time hard (NP-hard) problem in logistics domain. Time window based VRP is an extension of the problem. The basic problem is to identify optimal set of routes for a fleet of vehicles to traverse to deliver to a given set of customers in a specified time duration. The objective is to minimize the costs of traversed routes. This paper proposes a machine learning and TSP based cluster redistribution approach to solve the time window based VRP. The proposed approach consists of three phases: machine learning based cluster creation, TSP based cluster routes and cluster re-distribution. The results demonstrate the efficacy and optimality of the proposed solution. Keywords: Vehicle Routing Problem (VRP), Time window based VRP, Machine learning
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