To deliver goods to car factories, the car manufacturer Renault is daily facing a complex truck loading problem where various goods must be packed into a truck such that they fulfill different constraints. As trucks can deliver goods to different factories on the same tour, classes of items have been defined, where a class is associated with a delivery point. As the number of items and the standard deviation of the sizes of the items are significant, no exact algorithm is competitive. Tabu search and genetic algorithms are proposed to tackle this problem. The results show that the most effective method is a genetic algorithm. An extension is then proposed, which consists in tackling all the instances within a given time limit. For this extension, results show that a combination of the algorithms is the most powerful strategy.
Group for Research in Decision Analysis