Memetic Algorithms for the MinLA Problem

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. Key words: Memetic Algorithms, Linear Arrangement, Heuristics.

• Type: Conference
• Year: 2005
• Where: AE
• Authors: Eduardo Rodriguez-Tello, Jin-Kao Hao, Jose Torres-Jimenez
• Keywords: AE 2005, Local Search Operator, Memetic Algorithms, Simulated Annealing Algorithm