Multidimensional Knapsack Problem: A Fitness Landscape Analysis Export

@article{tavares:2008:tsmcb, abstract = {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.}, author = {Tavares, Jorge and Pereira, Francisco B. and Costa, Ernesto}, citeulike-article-id = {3008195}, journal = {IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cynernetics}, keywords = {analysis, heuristics, landscapes, mkp, representation}, month = {June}, number = {3}, pages = {604--616}, posted-at = {2008-07-16 13:15:29}, priority = {0}, publisher = {IEEE}, title = {Multidimensional Knapsack Problem: A Fitness Landscape Analysis}, volume = {38}, year = {2008} }

TY - JOUR ID - tavares:2008:tsmcb L3 - citeulike-article-id:3008195 N2 - 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. IS - 3 JF - IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cynernetics EP - 616 TI - Multidimensional Knapsack Problem: A Fitness Landscape Analysis PB - IEEE VL - 38 SP - 604 KW - analysis KW - heuristics KW - landscapes KW - mkp KW - representation AU - Tavares, Jorge AU - Pereira, Francisco AU - Costa, Ernesto PY - 2008/June// ER -