A tabu search heuristic for the vehicle routing problem
Management Science
Exact Solution of the Two-Dimensional Finite Bon Packing Problem
Management Science
The vehicle routing problem
A lower bound for the non-oriented two-dimensional bin packing problem
Discrete Applied Mathematics - Special issue: Third ALIO-EURO meeting on applied combinatorial optimization
A Savings Based Ant System For The Vehicle Routing Problem
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Heuristic and Metaheuristic Approaches for a Class of Two-Dimensional Bin Packing Problems
INFORMS Journal on Computing
The Three-Dimensional Bin Packing Problem
Operations Research
An Exact Approach to the Strip-Packing Problem
INFORMS Journal on Computing
D-Ants: savings based ants divide and conquer the vehicle routing problem
Computers and Operations Research
A New Placement Heuristic for the Orthogonal Stock-Cutting Problem
Operations Research
A Tabu Search Algorithm for a Routing and Container Loading Problem
Transportation Science
Reactive GRASP for the strip-packing problem
Computers and Operations Research
An Exact Approach for the Vehicle Routing Problem with Two-Dimensional Loading Constraints
Transportation Science
Computers and Operations Research
Computers and Operations Research
HM'10 Proceedings of the 7th international conference on Hybrid metaheuristics
Survey: matheuristics for rich vehicle routing problems
HM'10 Proceedings of the 7th international conference on Hybrid metaheuristics
A new geometric shape-based genetic clustering algorithm for the multi-depot vehicle routing problem
Expert Systems with Applications: An International Journal
A distribution network optimization problem for third party logistics service providers
Expert Systems with Applications: An International Journal
Efficient algorithms for the double traveling salesman problem with multiple stacks
Computers and Operations Research
Computers and Operations Research
The Pallet-Packing Vehicle Routing Problem
Transportation Science
Packing first, routing second-a heuristic for the vehicle routing and loading problem
Computers and Operations Research
Heuristics for the strip packing problem with unloading constraints
Computers and Operations Research
Computers and Operations Research
A GRASP×ELS for the vehicle routing problem with basic three-dimensional loading constraints
Engineering Applications of Artificial Intelligence
Survey of Green Vehicle Routing Problem: Past and future trends
Expert Systems with Applications: An International Journal
Two-dimensional strip packing with unloading constraints
Discrete Applied Mathematics
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In this paper a combination of the two most important problems in distribution logistics is considered, known as the two-dimensional loading vehicle routing problem. This problem combines the loading of the freight into the vehicles, and the successive routing of the vehicles along the road network, with the aim of satisfying the demands of the customers. The problem is solved by different heuristics for the loading part, and by an ant colony optimization (ACO) algorithm for the overall optimization. The excellent behavior of the algorithm is proven through extensive computational results. The contribution of the paper is threefold: first, on small-size instances the proposed algorithm reaches a high number of proven optimal solutions, while on large-size instances it clearly outperforms previous heuristics from the literature. Second, due to its flexibility in handling different loading constraints, including items rotation and rear loading, it allows us to draw qualitative conclusions of practical interest in transportation, such as evaluating the potential savings by permitting more flexible loading configurations. Third, in ACO a combination of different heuristic information usually did not turn out to be successful in the past. Our approach provides an example where an ACO algorithm successfully combines two completely different heuristic measures (with respect to loading and routing) within one pheromone matrix.