Abstract: Grouping problem exists widely in management, it is hard to solve because of its strong NP-Hard. This paper proposed number-coded grouping genetic algorithm, a new solution to supply logistics optimization problem with constraints and nonlinear objective function. Several grouping-based operators were designed to realize the grouping evolution, such as two-point grouping crossover and heuristic grouping mutation. It was applied to a real-world numerical case in transportation consolidation, which shows the performance of the algorithm.

Key words:  grouping genetic algorithm, grouping problem, supply logistics, transportation consolidation, joint replenishment