The multiple container packing problem: a genetic algorithm approach with weighted codings
ACM SIGAPP Applied Computing Review
The vehicle routing problem
Tabu Search
Genetic Algorithms for the Multiple Container Packing Problem
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
A parallel tabu search algorithm for solving the container loading problem
Parallel Computing - Special issue: Parallel computing in logistics
Stochastic Local Search: Foundations & Applications
Stochastic Local Search: Foundations & Applications
A GRASP Approach to the Container-Loading Problem
IEEE Intelligent Systems
A Tabu Search Algorithm for a Routing and Container Loading Problem
Transportation Science
A Maximal-Space Algorithm for the Container Loading Problem
INFORMS Journal on Computing
IEEE Transactions on Intelligent Transportation Systems
Neighborhood structures for the container loading problem: a VNS implementation
Journal of Heuristics
A Tree Search Algorithm for Solving the Container Loading Problem
INFORMS Journal on Computing
Two natural heuristics for 3D packing with practical loading constraints
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
Modern Applied Statistics with S
Modern Applied Statistics with S
Multi-container loading with non-convex 3D shapes using a GA/TS hybrid
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Local search techniques for a routing-packing problem
Computers and Industrial Engineering
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We consider a complex variant of the Container Loading Problem arising from a real-world industrial application. It includes several features such as multiple containers, box rotation, and bearable weight, which are of importance in many practical situations. In addition, it also considers the situation in which boxes have to be delivered to different destinations (multi-drop).Our solution technique is based on local search metaheuristics. Local search works on the space of sequences of boxes to be loaded, while the actual load is obtained by invoking, at each iteration, a specialized procedure called loader. The loader inserts the boxes in the container using a deterministic heuristic which produces a load that is feasible according to the constraints.We test our solver on real-world instances provided by our industrial partner, showing a clear improvement on the previous heuristic solution. In addition, we compare our solver on benchmarks from the literature on the basic container loading problems. The outcome is that the results are in some cases in-line with the best ones in the literature and for other cases they also improve upon the best known ones. All instances and solutions are made available on the web for future comparisons.