Milk-run methodology is proposed to manage the procurement of orders from suppliers. The heuristic solution methods in the literature generally apply stepwise approach to route and load the vehicles.
In this study we propose a hybrid genetic local search algorithm which simultaneous solves vehicle routing
and order loading problems. This is the main contribution of the study. We consider volume and weight capacities (multi capacitated) of different types of transportation vehicles (heterogeneous fleet). Because of high adaptability and easy utilization, genetic algorithms are the most preferred approach of meta-heuristics.
The chromosome structure of the proposed genetic algorithm is constituted by random numbers to eliminate
infeasibility. The best chromosome of each generation is improved using local search method during the
algorithm runs. We applied the algorithm to a real manufacturing company that produces welding robots and
other process automation equipment. The results showed the effectiveness of the algorithm
