Computers and Operations Research
Toward Self-Integrating Software Applications for Supply Chain Management
Information Systems Frontiers
A parallel tabu search algorithm for solving the container loading problem
Parallel Computing - Special issue: Parallel computing in logistics
A GRASP Approach to the Container-Loading Problem
IEEE Intelligent Systems
An efficient variable neighborhood search heuristic for very large scale vehicle routing problems
Computers and Operations Research
A Maximal-Space Algorithm for the Container Loading Problem
INFORMS Journal on Computing
A caving degree based flake arrangement approach for the container loading problem
Computers and Industrial Engineering
An efficient placement heuristic for three-dimensional rectangular packing
Computers and Operations Research
A hybrid 'bee(s) algorithm' for solving container loading problems
Applied Soft Computing
Three-dimensional container loading models with cargo stability and load bearing constraints
Computers and Operations Research
A parallel multi-population biased random-key genetic algorithm for a container loading problem
Computers and Operations Research
Expert Systems with Applications: An International Journal
Computers and Operations Research
A heuristic block-loading algorithm based on multi-layer search for the container loading problem
Computers and Operations Research
Packing first, routing second-a heuristic for the vehicle routing and loading problem
Computers and Operations Research
Local search for a multi-drop multi-container loading problem
Journal of Heuristics
A beam search approach to the container loading problem
Computers and Operations Research
Algorithms for the maximum k-club problem in graphs
Journal of Combinatorial Optimization
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This paper presents a Variable Neighborhood Search (VNS) algorithm for the container loading problem. The algorithm combines a constructive procedure based on the concept of maximal-space, with five new movements defined directly on the physical layout of the packed boxes, which involve insertion and deletion strategies.The new algorithm is tested on the complete set of Bischoff and Ratcliff problems, ranging from weakly to strongly heterogeneous instances, and outperforms all the reported algorithms which have used those test instances.