Saving-based algorithms are commonly used as inner mechanisms of efficient heuristic construction procedures. We present a general mechanism for enhancing the effectiveness of such heuristics based on a two-level genetic algorithm. The higher-level algorithm searches in the space of possible merge lists which are then used by the lower-level saving-based algorithm to build the solution. We describe the general framework and we illustrate its application to three hard combinatorial problems. Experimental results on three hard combinatorial optimization problems show that the approach is very effective and it enables considerable enhancement of the performance of saving-based algorithms.
|Journal||Engineering Applications of Artificial Intelligence|
|Early online date||4 Mar 2011|
|Publication status||Published - Jun 2011|
Battarra, M., Benedettini, S., & Roli, A. (2011). Leveraging saving-based algorithms by master–slave genetic algorithms. Engineering Applications of Artificial Intelligence, 24(4), 555-566. https://doi.org/10.1016/j.engappai.2011.01.007