Multidimensional knapsack problem: a fitness landscape analysis.
Fitness landscape analysis techniques are used to better understand the influence of genetic representations and associated variation operators when solving a combinatorial optimization problem. Five representations are investigated for the multidimensional knapsack problem. Common mutation operators, such as bit-flip mutation, are employed to generate fitness landscapes. Measures such as fitness distance correlation and autocorrelation are applied to examine the landscapes associated with the tested genetic encodings. Furthermore, additional experiments are made to observe the effects of adding heuristics and local optimization to the representations. Encodings with a strong heuristic bias are more efficient, and the addition of local optimization techniques further enhances their performance.
Tavares
Jorge
J
Center for Informatics and Systems, University of Coimbra, Department of Informatics Engineering, Coimbra, Portugal. jorge.tavares@ieee.org
Pereira
Francisco B
FB
Costa
Ernesto
E
D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D008962:Models, Theoretical; D012815:Signal Processing, Computer-Assisted