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Multi-container loading problems with multidrop and split delivery conditions
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DOI：10.1016/j.cie.2022.108844.png)
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This paper considers a multi-container loading problem in which each customer orders a set of pallets of different weights and the objective is to meet all orders with the minimum number of trucks. Strict constraints regarding stability, multidrop, and axle weight limits must be respected for each truck at each stop along the route. When assigning pallets to trucks, split delivery is allowed, even if each customer's order fits on a single truck. Determining the minimum number of trucks in container loading, considering realistic packing constraints and allowing for split delivery, is a challenging problem that has not been addressed in the literature. To solve it optimally, we first develop an integer linear model and then a decomposition procedure, combining relaxed integer models and heuristic algorithms. An extensive computational study on a new benchmark, varying the number of customers, the number of pallets, and the pallet weight configurations, showed that the integer linear model could only solve small instances, but the decomposition procedure was capable of efficiently solving all instances to optimality. The benchmark was also used to study the effect of split delivery on the solutions of the problem, determining in which cases it provides advantages compared to the non-split alternative in terms of feasibility and number of trucks.
Keyword:
Multi-container loading
Split delivery
Stability
Integer models
期刊
IF:
6.5
论文数:
1.0W
被引数:
3.8W
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