Weight-codings in a genetic algorithm for the multi-constraint knapsack problem

G.R. Raidl
Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406)  
This paper presents different variants of weight-coding in a genetic algorithm (GA) for solving the multiconstraint knapsack problem (MKP). In this coding, a chromosome is a vector of weights associated with the items of the MKP. The phenotype is obtained by using the weights to generate a modified version of the original problem and applying a decoding heuristic to it. Four techniques of biasing the original problem with weights are discussed. Two well working decoding heuristics, one based on
more » ... stics, one based on the surrogate relaxation and the other one based on the Lagrangian relaxation, are introduced. The different weight-coding variants are experimentally compared to each other using a steady-state GA. Furthermore, the influence of the biasing strength, a strategy parameter of the codings, is investigated. In general, the GA found solutions being substantially better than those obtained by applying heuristics to the MKP directly.
doi:10.1109/cec.1999.781987 fatcat:tdem4s7oo5dvrg6obabvz37zyu