Efficient scheduling of workflow applications represented by weighted directed acyclic graphs (DAG) on a set of heterogeneous processors is essential for achieving high performance. The optimization problem is NP-complete in general. A few heuristics for scheduling on heterogeneous systems have been proposed recently. However, few of them consider the case where processors have different capabilities. In this paper, we present a novel list scheduling based algorithm to deal with this situation. The algorithm (SDC) has two distinctive features. First, the algorithm takes into account the effect of Percentage of Capable Processors (PCP) when assigning the task node weights. For two task nodes with same average computation cost, our weight assignment policy tends to give higher weight to the task with small PCP. Secondly, during the processor selection phase, the algorithm adjusts the effective /Earliest Finish Time/ strategy by incorporating the average communication cost between the current scheduling node and its children. Comparison study shows that our algorithm performs better than related work overall.