Journal of Jilin University(Engineering and Technology Edition) ›› 2025, Vol. 55 ›› Issue (2): 631-638.doi: 10.13229/j.cnki.jdxbgxb.20231452

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Optimization method for emergency material delivery vehicle scheduling in multiple distribution centers based on multi-objective ant colony algorithm

Jian-hui LIU(),Qiong WANG   

  1. School of Mechanical and Electrical Engineering，Xi'an University of Architecture&Technology，Xi 'an 710055，China
  • Received:2023-12-28 Online:2025-02-01 Published:2025-04-16

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Abstract:

In order to effectively solve the problems of poor vehicle scheduling scheme and low satisfaction of materials in multi-distribution center， a multi-objective ant colony algorithm based vehicle scheduling optimization method for multi-distribution center emergency materials distribution was proposed. Considering the actual situation of the distribution route， aiming at maximizing the average transportation time and material satisfaction， the multi-objective function of vehicle scheduling optimization for emergency materials distribution in multi-distribution centers was constructed. Based on the multi-objective ant colony algorithm， the optimal vehicle scheduling scheme for emergency materials distribution in multi-distribution center is determined. The experimental analysis proves that the proposed multi-distribution center emergency materials distribution scheme is more reasonable， the scheduling comprehensive coefficient is above 0.950， and the material satisfaction rate is above 90.00%， which effectively improves the vehicle scheduling effect and can develop a more reasonable scheduling scheme.

Key words: multi objective ant colony algorithm, multiple distribution centers, emergency material distribution, vehicle scheduling optimization

CLC Number: 

  • F252

Fig. 1

Distribution of distribution centers and disaster sites"

Table 1

Distribution vehicle scheduling optimization method parameters"

序号参数数值
1uik100
2k10
3M1.024
4α1.143
5ρ（0，1）
6ε0.651

Table 2

Multi-objective ant colony algorithm solves the feasible solution"

测试指标预期目标多目标蚁群算法
平均最优解1 7021 578
最优解/车辆数1 464/41 355/3
平均解1 7791 635
平均偏差0.1770.171
最大偏差0.2630.224
运算时间/s46.8241.55
平均运算时间/s40.1137.25

Fig.2

Comparison of emergency material delivery vehicle scheduling schemes for multiple distribution centers using different methods"

Table 3

Comprehensive scheduling coefficient of emergency materials distribution vehicle scheduling scheme in multi-distribution centers"

调度方案调度综合系数
本文方法文献［3］方法文献［4］方法
10.9570.9120.845
20.9710.9050.901
30.9590.9110.867

Fig.3

Comparison of material satisfaction rate of different dispatching methods"

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