Abstract :
This paper introduces a computational model simulating the dynamic process of human immune response to solve multidimensional knapsack problems. The new model is a quaternion (G, I, R, At), where G denotes exterior stimulus or antigen,denotes the set of valid antibodies, R denotes the set of reaction rules describing the interactions between antibodies, and Al denotes the dynamic algorithm describing how the reaction rules are applied to antibody population. The set of antibody-adjusting rules, the set of clonal selection rules, and a dynamic algorithm, named MKP-PAISA, are designed for solving multidimensional knapsack problems. The efficiency of the proposed algorithm was validated by testing on 57 benchmark problems and comparing with three genetic algorithms. The results indicated that the proposed algorithm was suitable for solving multidimensional knapsack problems.
Keywords :
genetic algorithms; knapsack problems; antibodies; antibody-adjusting rules; antigen; clonal selection rules; computational model; dynamic algorithm; exterior stimulus; genetic algorithms; human immune response; immune-inspired algorithm; multidimensional knapsack problems; reaction rules; Evolutionary computation; Multidimensional systems; Testing;
