The proposed method is tested on a large family of instances, including a real-world instance; the computational results obtained show the effectiveness of the different components of the algorithm.
The computational results, on two sets of instances taken from the literature, show the effectiveness of the proposed algorithm.
Extensive experiments, based on randomly generated instances of different sizes and characteristics, show the effectiveness of the method compared with a state-of-the-art solver.
Extensive computational experiments on randomly generated instances with up to 400 locations and 5 products show the effectiveness of the approach.
A 1999 experiment purporting to show the effectiveness of shooting coyotes from helicopters, for instance, had a higher density of sheep in its control pastures, which could have made them more attractive to hungry coyotes.
Further experimental results on comparing CCEHC with a state-of-the-art complete solver show the effectiveness of CCEHC on a number of application WPMS instances, and indicate that CCEHC might be beneficial in practice.
The empirical results show the effectiveness of the proposed method and strategies in finding near optimal solutions to these very large instances at a reasonably small computational effort.
Numerical results show the effectiveness of the proposed scheme.
Our experiments show the effectiveness of the proposed methods.
Analytics tools show the effectiveness and return on investment of the social media outreach.
