Modern heuristic techniques for combinatorial problems
The sciences of the artificial (3rd ed.)
The sciences of the artificial (3rd ed.)
Tabu Search
| Hi-index | 0.00 |
Combinatorial optimization problems are embedded in dynamic environments, spanning many domains. As these problem environments may change repeatedly, agents that attempt to solve problems in such environments must be able to adapt to each change that occurs. We present a technique for a Tabu Search-based meta-heuristic agent that collaborates with a truth maintenance agent to maximize reuse of generated solutions that may become partially inconsistent when a change occurs in the problem space. By allowing the truth maintenance agent to perform partial plan repairs, we hope to mitigate the effect that a change has on the performance of the planning agent. Such a system is discussed in a global logistics scheduling program. The performance of our approach is analyzed with respect to a dynamic constrained vehicle routing problem. Our results show that partial plan repairs increase the stability of solutions in dynamic domains.