An Activity-Based Travel Personalization Tool Driven by the Genetic Algorithm

Table 3

The results of user A’s daily activity chain optimization.

User A
The best-fit solution offered			The best-fit solution of the alternative modes
Cycling			PT + walking			Car
The IDs of the activities in an order	Start time	End time	The IDs of the activities in an order	Start time	End time	The IDs of the activities in an order	Start time	End time
0		08:45	0 M		08:00	0		08:00
1	09:00	14:00	6 T	08:03	08:23	6	08:01	08:21
2	14:30	15:15	1 T	09:00	14:00	1	09:00	14:00
6	15:17	15:37	5 W	14:05	14:25	2	14:30	15:15
5	15:37	15:57	2 W	14:30	15:15	4	15:16	15:46
3	16:02	16:32	4 M	15:16	15:46	3	15:46	16:16
4	16:32	17:02	3 W	15:48	16:18	5	16:18	16:38
7	17:09		7	16:19		7	16:41
Total absolute travel time: 42 minutes			Total absolute travel time: 24.2 minutes			Total absolute travel time: 31.7 minutes
Estimated congestion delay: 0 minute			Estimated congestion delay: 0 minute			Estimated congestion delay: 17.52 minutes
Estimated out-vehicle time: 0 minute			Estimated out-vehicle time: 15 minutes			Estimated out-vehicle time: 0 minute
Utility score: 4038.2			Utility score: 1559.9			Utility score: 893.3

M = metro, T = tram, W = walking;  = flexible location priority.