Abstract
The optimization of material distribution is of great importance on shipbuilding project, which determines whether the production capacity of the ship is fully embodied. A workstation-oriented material distribution problem is formulated with reference to the production characteristics of shipyards. This problem can be considered as a complex vehicle routing problem (VRP) with capacity constraints, time windows and multiple distribution centers. In order to minimize the impact of distribution problems on production, a multi-population genetic algorithm (MPGA) that can minimize the sum of earliness and tardiness penalties is proposed in this paper. The proposed algorithm looks for near-optimal solutions for assigning distribution tasks and optimizing vehicle routing. Then, the evaluation of the solutions generated with MPGA is achieved with a priority-based heuristic algorithm. Simulation results of different cases show that the proposed MPGA allows logistics distribution system to operate more efficiently and solutions can be improved by 71% on average compared to those obtained with the traditional priority rule method.
Highlights
Material preparation is a prerequisite for shipbuilding
The object function value gained by multi-population genetic algorithm (MPGA) improves by an average of 71% over that of priority-based heuristic algorithm, which is a significant improvement in actual application
We dealt with the workstation-oriented distribution problem of shipbuilding materials, which can be considered as a complex vehicle routing problem
Summary
Material preparation is a prerequisite for shipbuilding. The refined production management under the modern shipbuilding mode puts forward higher requirements for the logistics and distribution of shipbuilding materials. The workstation-oriented distribution problem of shipbuilding materials is a complex vehicle routing problem (VRP). The materials are classified according to the demand of the workstations They researched the material distribution optimization with hard time windows from the point of material storage and delivery. Chen et al.[2] introduced the concept of fuzzy time window into VRP They analyzed several optimization objectives, such as fleet size, average customer satisfaction, transportation distance and queuing time. Considering the change of material demand caused by the production fluctuations, Yan Zhengfeng et al.[6] established a path optimization model of workshop logistics based on fuzzy soft time windows, and solved the model with dynamic programming simulated annealing algorithm. The following section gives a precise description to the workstation-oriented distribution problem of shipbuilding materials.
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