In this paper, we propose a new traffic engineering (TE) approach for software-defined Internet Service Provider (SD-ISP) networks that strives to maximize the network throughput and provide adequate QoS (Quality of Service) with a minimal reconfiguration cost. In contrast to the conventional TE approaches, which perform the network optimizations periodically and control the side effects of reconfigurations by carefully choosing the period length between the optimization cycles, we use a bi-objective optimization model that minimizes maximum link utilization and the reconfiguration overhead. A new heuristic algorithm has been proposed in order to generate the approximated Pareto frontier for the bi-objective optimization model, while the Lyapunov drift-plus-penalty algorithm is used to select the most appropriate solution from the approximated Pareto set. Our simulation study shows that the proposed approach adjusts to the ISP's constraint on time-average reconfiguration rate by trading the throughput performance efficiently. Since the reconfiguration overhead is reduced, the network controller could be allowed to optimize resource allocation more frequently, in order to quickly and efficiently respond to the network changes. The paper analyses the impact of the reconfiguration rate constraint, average flow duration and the frequency of TE on the overall network performance.