Abstract
We demonstrate the use of Ant Colony System (ACS) to solve the capacitated
vehicle routing problem associated with collection of recycling waste from
households, treated as nodes in a spatial network. For networks where the
nodes are concentrated in separate clusters, the use of k-means clustering can
greatly improve the eciency of the solution. The ACS algorithm is extended
to model the use of multi-compartment vehicles with kerbside sorting of waste
into separate compartments for glass, paper, etc. The algorithm produces
high-quality solutions for two-compartment test problems.
vehicle routing problem associated with collection of recycling waste from
households, treated as nodes in a spatial network. For networks where the
nodes are concentrated in separate clusters, the use of k-means clustering can
greatly improve the eciency of the solution. The ACS algorithm is extended
to model the use of multi-compartment vehicles with kerbside sorting of waste
into separate compartments for glass, paper, etc. The algorithm produces
high-quality solutions for two-compartment test problems.
| Original language | English |
|---|---|
| Pages (from-to) | 169-176 |
| Number of pages | 8 |
| Journal | Applied Soft Computing |
| Volume | 15 |
| Early online date | 4 Nov 2013 |
| DOIs | |
| Publication status | Published - 1 Feb 2014 |
Keywords
- ant colony optimization
- capacitated vehicle routing problem
- clustering