Genetic Algorithms for Solving Combinatorial Mass Balancing Problem

A problem of placing discretely distributed masses of objects on fixed locations minimizing the unbalance of the system is considered. The problem is formulated as Euclidean combinatorial optimization one on the permutation set induced by given masses. To solve this problem, original genetic algorithms are offered, for which approaches to a formation of crossover and mutation operators are described. The algorithms are tested on various problems of balancing discretely distributed masses, including those where the objects' rotation is permitted.