Multi-objective transportation optimization based on Lam-GA

A new genetic algorithm based on the theory of lamarckian evolution (Lam-GA) to solve multi-objective transportation optimization problem(MOTP) is presented in the paper. The algorithm carries through some local mutation according to certain rules after distributing transportation counts on the fuzzy rule basis, which can increase the intensity for searching better solution. Experimental data shows that after strengthening the mutation locally, the new algorithm can get better Pareto front and Pareto optimal solutions in solving large-scale transport problems, so that Lam-GA is more effective than Fuzzy-GA, st-GA and m-GA. It demonstrates also that lamarckian evolutionary theory is important for guiding significantly in solving practical problems.