PDPTW instances

PDPTW/README.md

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+# PDPTW
+
+This folder contains pickup and delivery problem with time windows (PDPTW) instances from two benchmark sets: Li & Lim (2003) and Sartori & Buriol (2020).
+The original instances are modified to fit PyVRP's VRPLIB format.
+The solution cost represents the total distance traveled.
+All files were retrieved on 8 July 2026.
+
+The instances are organised into two top-level folders, `li/` and `sartori/`, each with a subfolder per instance size.
+
+## Li & Lim
+
+The `li/` folder contains the Li & Lim (2003) instances with 100, 200, 400, 600, 800 and 1000 customers.
+Downloaded from [SINTEF](https://www.sintef.no/projectweb/top/pdptw/li-lim-benchmark/) and converted from the Solomon-style format.
+Distances are Euclidean and follow PyVRP's `exact` convention: each edge distance is scaled by 1000 and rounded to the nearest integer.
+The best-known solutions (BKS) are taken from the [SINTEF](https://www.sintef.no/projectweb/top/pdptw/) solution pages.
+Two solutions did not have an explicit solution file: `lc1_4_4` and `lc2_4_4`.
+We used multiple solvers to find the best-known solution for these two instances.
+
+## Sartori & Buriol
+
+The `sartori/` folder contains the Sartori & Buriol (2020) instances with 100 up to 5000 customers.
+The instances are downloaded from the [Mendeley dataset](https://data.mendeley.com/datasets/wr2ct4r22f/2) and the solutions from the [companion GitHub repository](https://github.com/cssartori/pdptw-instances).
+These instances provide an explicit integer distance matrix, so PyVRP's `none` rounding convention is used and distances are taken directly from the instance data.
+
+### References
+
+Li, H., & Lim, A. (2003). A metaheuristic for the pickup and delivery problem with time windows. International Journal on Artificial Intelligence Tools, 12(2), 173–186. https://doi.org/10.1142/S0218213003001186
+
+Sartori, C. S., & Buriol, L. S. (2020). A study on the pickup and delivery problem with time windows: matheuristics and new instances. Computers & Operations Research, 124, 105065. https://doi.org/10.1016/j.cor.2020.105065

PDPTW/li/100/lc101.sol

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+Route #1: 81 78 104 76 71 70 73 77 79 80
+Route #2: 57 55 54 53 56 58 60 59
+Route #3: 98 96 95 94 92 93 97 106 100 99
+Route #4: 13 17 18 19 15 16 14 12
+Route #5: 32 33 31 35 37 38 39 36 105 34
+Route #6: 90 87 86 83 82 84 85 88 89 91
+Route #7: 43 42 41 40 44 46 45 48 51 101 50 52 49 47
+Route #8: 67 65 63 62 74 72 61 64 102 68 66 69
+Route #9: 5 3 7 8 10 11 9 6 4 2 1 75
+Route #10: 20 24 25 27 29 30 28 26 23 103 22 21
+Cost 828937

PDPTW/li/100/lc101.vrp

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+NAME: lc101
+TYPE: PDPTW
+COMMENT: Li & Lim PDPTW benchmark converted from SINTEF format
+DIMENSION: 107
+VEHICLES: 25
+CAPACITY: 200
+EDGE_WEIGHT_TYPE: EUC_2D
+NODE_COORD_SECTION
+0 40 50
+2 45 68
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+TIME_WINDOW_SECTION
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+8 170 225
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+PICKUP_AND_DELIVERY_SECTION
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+104 -10 732 777 90 24 0
+105 -20 109 170 90 79 0
+106 -10 665 716 90 37 0
+107 -30 561 622 90 98 0
+DEPOT_SECTION
+1
+-1
+EOF

PDPTW/li/100/lc102.sol

@@ -0,0 +1,11 @@
+Route #1: 81 78 105 76 71 70 73 77 79 80
+Route #2: 57 55 54 53 56 58 60 59
+Route #3: 98 96 95 94 92 93 97 101 100 99
+Route #4: 32 33 31 35 37 38 39 104 36 34
+Route #5: 13 17 18 19 15 16 14 12
+Route #6: 90 87 86 83 82 84 85 88 89 91
+Route #7: 43 42 41 40 44 46 45 48 51 50 106 52 49 47
+Route #8: 67 65 63 62 74 72 61 64 68 102 66 69
+Route #9: 5 3 7 8 10 11 9 6 4 2 1 75
+Route #10: 20 24 25 27 29 30 28 103 26 23 22 21
+Cost 828937