Memetic Algorithms for the MinLA Problem [chapter]

Eduardo Rodriguez-Tello, Jin-Kao Hao, Jose Torres-Jimenez
2006 Lecture Notes in Computer Science  
This paper presents a new Memetic Algorithm designed to compute near optimal solutions for the MinLA problem. It incorporates a highly specialized crossover operator, a fast MinLA heuristic used to create the initial population and a local search operator based on a fine tuned Simulated Annealing algorithm. Its performance is investigated through extensive experimentation over well known benchmarks and compared with other state-of-the-art algorithms.
doi:10.1007/11740698_7 fatcat:7q2ddbttyvfqlkkxgapp3gsijm