[−][src]Module vrp_core::models::matrix
Contains functionality to work with solution represented in adjacency matrix from.
This is experimental functionality with a main purpose to design more sophisticated metaheuristics which capable to produce *unfeasible solutions and convert them to feasible.
*unfeasible solution is solution which has at least one violation of hard constraint.
Encoding schema:
For each job in plan create a tuple: single -> places -> times : (job, 0, place_index, time_window_index) multi -> singles-> places-> times -> (job, single_index, place_index, time_window_index) => assign unique index
For each actor in fleet create a tuple: actors -> (start, time), (end, time) -> unique => assign unique index (agreed indexing within jobs)
Example:
from problem: actors: a b c activities: (01) 02 03 04 05 06 07 08 09 (10) where (01) and (10) - depots (start and end)
routes with their activities in solution: a: 01 03 06 08 10 b: 01 07 04 10 c: 01 09 05 02 10
adjacency matrix: 01 02 03 04 05 06 07 08 09 10 01 a b c 02 c 03 a 04 b 05 c 06 a 07 b 08 a 09 c 10
Structs
| AdjacencyMatrixDecipher | Provides way to encode/decode solution to adjacency matrix representation. |
| SparseMatrix | A simple |
Traits
| AdjacencyMatrix | An adjacency matrix trait specifies behaviour of a data structure which is used to store VRP solution. |