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Optimization of Multi-Cycle Distribution of Emergency Perishable Materials Based on a Two-Stage Algorithm Under Demand Fuzzy
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DOI：10.3390/app16073519.png)
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Abstract
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Post-disaster emergency perishable material distribution is an essential part of emergency relief, which is of great significance to reducing disaster losses and casualties and improving rescue efficiency. However, in actual rescue, the demand information of disaster sites is often complex to determine, and the demand for emergency perishable materials needs to be clarified. Therefore, the single-cycle distribution makes it difficult to meet the demand for emergency perishable materials at disaster sites. To effectively improve the efficiency of emergency relief, this paper constructs a distribution optimization model with a multi-cycle vehicle path and the dual objectives of minimizing the distribution delay penalty and corruption cost and minimizing the unsatisfied demand. Initially, the fuzzy demand is addressed through the application of triangular fuzzy numbers and the most probable value weighting method. Following this, a two-stage optimization algorithm is devised by integrating the K-means++ algorithm with an enhanced Differential Evolutionary Whale Optimization Algorithm (DE-WOA). This algorithm operates by first clustering the affected points and subsequently solving the multi-objective model, thereby providing a robust methodology and strategic recommendations for the distribution of perishable materials across diverse scenarios. Our study reveals that the multi-objective model developed in this paper exhibits remarkable operability and practicality in the distribution of post-disaster emergency perishable materials, as evidenced by the verification via numerical examples. Through a comparison with the single-stage whale optimization algorithm, it is evident that the enhanced two-stage differential evolutionary whale optimization algorithm not only demonstrates a substantially faster convergence rate and a superior solution quality but also proves to be more suitably adapted to the proposed model. Significantly, the overall optimization performance has been augmented by 33%, thereby providing further substantiation of the efficacy of the designed improved algorithm.
Keywords:
emergency material distribution
multi-cycle
demand fuzzy
perishable materials
K-means plus plus
whale optimization algorithm
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