Many real-world optimization problems usually require a large number of conflicting objectives to be optimized simultaneously to obtain solution. It has been observed that these kinds of many-objective optimization problems often pose several performance challenges to the traditional multi-objective optimization algorithms. To address the performance issue caused by the different types of MaOPs, recently, a variety of many-objective particle swarm optimization has been proposed. However, external archive maintenance and selection of leaders for designing the MaOPSO to real-world MaOPs are still (...) challenging issues. This work presents a MaOPSO based on entropy-driven global best selection strategy to solve the many-objective software package restructuring problem. EMPSO makes use of the entropy and quality indicator for the selection of global best particle. To evaluate the performance of the proposed approach, we applied it over the five MaOSPR problems. We compared it with eight variants of MaOPSO, which are based on eight different global best selection strategies. The results indicate that the proposed EMPSO is competitive with respect to the existing global best selection strategies based on variants of MaOPSO approaches. (shrink)

The issue of ‘mandatory publications’ has generated serious flak about its usefulness among the various stakeholders. A lot of debate centers around the question of ‘lack of will’ or ‘lack of skill’ as a reason for the diminishing research interests among the medical faculty in India. In our view, it is the lack of will to publish good quality research which is to be blamed rather than the lack of skill to do good quality research.