The current goods distribution planning still has limitations in its operational policies. Many decision makers do calculations based on static (past) data to determine the distribution policy over time, while demand is probabilistic since it changes over time. In addition, many researches on distribution and routing have implemented various deterministic and heuristic approaches. The present study attempts to measure to what extend heuristic solutions can overcome changes in goods demand. This study uses sequential insertion algorithms with 1-0 relocation to get the optimal solution, then computer simulation techniques are used to determine the ability of the solution to overcome the probabilistic demand. The effect of capacity reduction (k=5% and k=10%) on heuristic-generated solutions under probabilistic demand is also discussed. Based on a numerical example with k = 10%, the route solution from sequential insertion is able to overcome the probabilistic demand.