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Design of intelligent logistics path planning algorithm for operations research

  
17 mar 2025
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Figure 1.

Flow chart of ant colony algorithm
Flow chart of ant colony algorithm

Figure 2.

Global pheromone update procedure
Global pheromone update procedure

Figure 3.

Traditional ant colony algorithm vehicle distribution path map
Traditional ant colony algorithm vehicle distribution path map

Figure 4.

Improved ant colony algorithm vehicle distribution path map
Improved ant colony algorithm vehicle distribution path map

Figure 5.

Traditional ant colony algorithm assembly
Traditional ant colony algorithm assembly

Figure 6.

Improved ant colony algorithm assembly
Improved ant colony algorithm assembly

Figure 7.

The comparison of the convergence of ant colony algorithm is improved
The comparison of the convergence of ant colony algorithm is improved

Figure 8.

The shortest path convergence of ant colony algorithm is improved
The shortest path convergence of ant colony algorithm is improved

Figure 9.

The vehicle distribution path that does not consider customer value
The vehicle distribution path that does not consider customer value

Figure 10.

Consider the customer’s value of vehicle distribution
Consider the customer’s value of vehicle distribution

Optimize the path result of the first car before

First car
Service node 1 16 4 6 5 2 1
Arrival discharge 0 0 0.5 3 3.3 4.5 5.9
Discharge discharge 0 0.9 3 3.4 4.5 5.9 5.90
Service start time 300 303.32 314.78 336.86 354.58 368.27 387.86
Service end time 300 314.52 336.86 352.91 368.01 385.31 387.86
The distance from the previous service node 0 54.31 64.55 1.55 6.75 7.26 108.51

The path result of the fourth car after optimization

Fourth car
Service node 1 6 4 11 10 7 15 1
Arrival discharge 0 0 1.3 2.8 3.3 5.1 6 6.7
Discharge discharge 0 1.3 2.8 3.3 5.1 6 6.7 6.7
Service start time 300 304.82 319.86 342.11 352.16 370.30 379.45 394.82
Service end time 300 319.81 341.86 352.11 370.16 379.30 392.45 394.82
The distance from the previous service node 0 114.00 2.14 11.00 3.44 6.00 7.00 97.21

Relevant symbols and definitions

Symbol Define
Lc Cargo damage assembly
Pc Cost of punishment due to timeout window
Ec Energy cost
Fc Fixed assembly
Ac Distribution assembly
Tc Transport assembly
Dc Unit distance transportation cost
Fk A fixed cost of distribution
Dij Customer point I to j
v1 Unit price of product
v2 The price of the product
Qik The vehicle reaches the customer point I after the remaining product quantity
ω1 Unit time loss coefficient
ω2 Unit time loss coefficient
Pik The total amount of the customer point I
Tik The vehicle is arriving at the customer point I
Tijk The loading time of the vehicle at the customer point j
Ec The cost of fuel consumption generated by vehicle distribution
Ec1 The cost of fuel consumption in the vehicle
Ec2 Fuel consumption cost per unit time
μ1 The vehicle reaches the customer point penalty coefficient in advance
μ2 The penalty coefficient of the vehicle late to the customer’s point
Cpi Customer point I’s penalty cost
[E,L] Specified delivery time window
[ET,LT] Acceptable delivery time window

The path result of the first car after optimization

First car
Service node 1 22 23 26 17 24 1
Arrival discharge 0 0 1.6 3.1 4.1 5.1 6.2
Discharge discharge 0 1.6 3.1 4.1 5.1 6.2 6.2
Service start time 300 304.21 324.31 342.39 351.52 367.65 384.75
Service end time 300 324.21 342.31 351.39 367.55 382.65 384.75
The distance from the previous service node 0 89.41 5.56 5.56 6.41 5.00 87.00

Don’t consider customer value satisfaction

Satisfaction <50% 50%<= Satisfaction<80% 80%<= Satisfaction<100% Satisfaction 100%
<80% <100%
r 18% 35% 18% 29%
SS 58% 10% 21% 11%

The path result of the second car after optimization

Second car
Service node 1 13 21 30 31 27 1
Arrival discharge 0 0 1.9 2.6 4.2 6 7
Discharge discharge 0 1.9 2.6 4.2 6 7 7
Service start time 300 304.42 325.61 334.71 352.81 380.06 397.31
Service end time 300 325.42 334.61 352.71 378.81 395.06 397.31
The distance from the previous service node 0 94.78 10.78 4.56 6.00 10.28 91.31

Optimize the path result of the fourth car before

Fourth car
Service node 1 18 28 12 9 1
Arrival discharge 0 0 1.5 3.0 4.3 5.6
Discharge discharge 0 1.6 2.9 4.2 5.6 5.6
Service start time 300 303.45 323.51 345.88 368.11 391.55
Service end time 300 323.26 345.51 367.88 390.11 391.55
The distance from the previous service node 0 68.02 6.04 9.12 3.73 61.15

The average satisfaction of different customer categories

Focus on customers Consolidated customer Maintenance customer Chicken ribs
r 73.12% 83.61% 76.41% 67.18%
SS 92.51% 61.45% 53.56% 45.66%

The path result of the sixth car after optimization

Sixth car
Service node 1 18 12 9 14 16 1
Arrival discharge 0 0 1.7 3.1 4.2 6 6.8
Discharge discharge 0 1.7 3.1 4.2 6 6.8 6.8
Service start time 300 302.71 323.81 345.86 368.06 383.53 394.84
Service end time 300 323.71 345.81 367.86 383.06 393.53 394.84
The distance from the previous service node 0 68.12 5.14 3.91 9.00 21.12 55.41

The path result of the fifth car after optimization

Fifth car
Service node 1 25 29 19 20- 28 1
Arrival discharge 0 0 1.9 3.1 4.1 5.1 6.5
Discharge discharge 0 1.9 3.1 4.1 5.1 6.5 6.5
Service start time 300 304.82 338.41 351.51 372.75 395.75 397.41
Service end time 300 326.32 5.00 6.00 9.66 41.88 68.51
The distance from the previous service node 0 92.75 5.00 6.00 10.54 41.9 2 68.45

Details of customer points

Serial number x-coordinate y-coordinate Demand Service time Time window Acceptable time window
1 402 61
2 495 14 1.6 16 [7:30,9:00] [7:00,9:30]
3 498 7 1.8 32 [6:00,8:00] [5:30,8:30]
4 498 2 1.3 20 [6:30,8:30] [6:00,9:00]
5 492 8 1.1 13 [8:00,9:00] [7:30,9:30]
6 496 3 1.2 13 [7:00,9:00] [6:30,9:30]
7 486 7 0.7 8 [7:40,10:20] [7:10,10:50]
8 496 23 1.4 18 [8:30,9:00] [8:00,9:30]
9 435 13 1.6 20 [7:30,9:00] [7:00,9:30]
10 486 5 1.4 16 [6:30,8:30] [6:00,9:00]
11 487 0.6 0.6 8 [6:30,9:00] [6:00,9:30]
12 436 8 1.4 20 [7:00,9:00] [6:30,9:30]
13 482 25 1.9 19 [8:00,9:00] [7:30,9:30]
14 435 5 1.3 13 [7:00,9:00] [6:30,9:30]
15 480 10 0.9 11 [7:30,9:00] [7:00,9:30]
16 437 20 0.8 8 [7:00,10:00] [6:30,10:30]
17 478 21 1.3 14 [7:30,9:00] [7:00,9:30]
18 441 7 1.5 18 [8:30,10:00] [8:00,10:30]
19 479 5 0.8 10 [7:00,8:30] [6:30,9:00]
20 482 -3 1.4 20 [8:30,9:00] [8:00,9:30]
21 489 30 0.9 7 [8:00,10:00] [7:30,10:30]
22 481 26 1.6 18 [6:00,8:30] [5:30,9:00]
23 478 24 1.4 16 [6:30,9:00] [6:00,9:30]
24 474 16 1 13 [7:00,9:00] [6:30,9:30]
25 474 5 1.7 20 [6:00,10:00] [5:30,10:30]
26 476 21 0.8 8 [6:30,8:00] [6:00,8:30]
27 486 32 1 14 [6:30,8:00] [6:00,8:30]
28 445 8 1.7 20 [8:30,11:00] [8:00,11:30]
29 474 2 0.7 11 [8:30,10:00] [8:00,10:30]
30 491 32 1.4 16 [8:00,9:00] [7:30,9:30]
31 494 37 1.6 25 [6:30,8:00] [6:00,8:30]

Optimize the path result of the fifth car before

Fifth car
Service node 1 31 8 15 3 29 1
Arrival discharge 0 0 1.6 2.8 4.6 6.2 7
Discharge discharge 0 1.6 2.8 4.6 6.2 7 7
Service start time 300 304.51 331.86 352.43 365.81 396.41 410.70
Service end time 300 331.33 351.81 365.43 395.81 409.41 410.70
The distance from the previous service node 0 97.91 15.15 24.41 18.00 24.62 94.45

The path result of the third car is optimized

Third car
Service node 1 8 2 3 5 1
Arrival discharge 0 0 1.6 3.9 5.6 6.1
Discharge discharge 0 1.6 3.9 5.6 6.1 6.1
Service start time 300 304.61 324.93 343.00 373.24 391.80
Service end time 300 324.61 342.93 373.00 388.24 391.80
The distance from the previous service node 0 104.51 15.06 5.27 6.41 108.77

Distribution of vehicle distribution

Delivery number Delivery path Load quantity Loading rate□□
1 0-91-70-54-61-87-55-0 98 98%
2 0-81-90-93-96-58-65-68-0 97 97%
3 0-66-83-98-95-57-65-67-0 100 100%
4 0-69-62-82-56-97-95-72-0 98 98%
5 0-95-68-52-36-76-0 100 100%
6 0-84-24-21-50-27-63-85-0 97 97%
7 0-71-100-5-47-0 75 75%
8 0-13-79-75-48-78-30-0 99 99%
9 0-21-24-22-47-26-0 100 100%
10 0-8-9-7-47-4-1-15-0 100 100%
11 0-83-55-77-91-0 94 94%
12 0-73-43-39-45-45-40-0 97 97%
13 0-3-6-37-19-34-0 100 100%
14 0-43-41-37-38-31-0 100 100%
15 0-13-16-17-11-14-0 100 100%
16 0-32-28-27-29-33-0 98 98%
17 0-32-28-27-30-33-0 91 91%
18 0-60-98-18-0 76 76%

Satisfaction ratio

Satisfaction<50% 50%<= Satisfaction<80% 80%<= Satisfaction<100% Satisfaction= 100%
<80% <100%
r 24% 31% 18% 27%
SS 45% 12% 13% 30%

Optimize the path result of the second car

Second car
Service node 1 26 17 21 27 30 14 1
Arrival discharge 0 0 0.8 1.9 2.6 3.6 4.8 5.9
Discharge discharge 0 0.8 1.9 2.6 3.6 4.8 5.9 5.9
Service start time 300 303.12 312.27 328.71 337.82 352.93 372.45 389.21
Service end time 300 312.12 328.27 337.71 352.82 371.93 387.55 389.21
The distance from the previous service node 0 86.45 6.41 18.42 4.71 6.22 65.53 66.81

Optimize the path result of the third car

Third car
Service node 1 24 13 23 22 1
Arrival discharge 0 0 1 2.9 4.1 5.5
Discharge discharge 0 1 2.9 4.1 5.5 5.5
Service start time 300 305.16 319.46 340.76 358.71 381.66
Service end time 300 319.16 340.46 358.76 378.71 381.66
The distance from the previous service node 0 87.00 13.04 8.57 4.67 89.27

The path result of the first sixth car

Sixth car
Service node 1 11 20 10 25 19 7 1
Arrival discharge 0 0 0.9 2.1 4.5 5.2 5.8 6.2
Discharge discharge 0 0.9 2.1 4.5 5.2 5.8 6.2 6.2
Service start time 300 304.71 314.85 337.08 355.41 379.52 388.75 399.24
Service end time 300 314.71 336.85 337.08 379.41 389.52 398.75 399.24
The distance from the previous service node 0 106.89 8.24 9.67 13.59 7.24 9.51 100.54
Lingua:
Inglese
Frequenza di pubblicazione:
1 volte all'anno
Argomenti della rivista:
Scienze biologiche, Scienze della vita, altro, Matematica, Matematica applicata, Matematica generale, Fisica, Fisica, altro