Meta-heuristics are commonly applied to solve various global optimization problems. In order make the meta-heuristics performing a search, balancing their exploration and ability is still an open avenue. This manuscript proposes novel Opposition-based learning scheme, called “PCOBL” (Partial Centroid Learning), inspired by partial centroid. PCOBL aims improve performance through maintaining eff...

This work investigates the performance of Differential Evolution (DE) and its opposition-based version (ODE) on large scale optimization problems. Opposition-based differential evolution (ODE) has been proposed based on DE; it employs opposition-based population initialization and generation jumping to accelerate convergence speed. ODE shows promising results in terms of convergence rate, robus...

background: video-based instruction has been stated as an effective method of teaching and its potentials have encouraged instructors learners to opt this method purpose: the current study has compared the students' cognitive learning in the two approaches of lecture- based and video-based teaching. methods: this quasi-experimental study was conducted on 88 senior nursing students who were rand...

This paper presents a modified Differential Evolution (DE) algorithm called OCMODE for solving multi-objective optimization problems. First, the initialization phase is improved by using the opposition based learning. Further, a time varying scale factor F employing chaotic sequence is used which helps to get a well distributed Pareto front by the help of non dominated and crowding distance sor...

We propose a new way of embedding shape distributions in a topological deformable template. These distributions rely on global shape descriptors corresponding to the 3D moment invariants. In opposition to usual Fourier-like descriptors, they can be updated during deformations at a relatively low cost. The moment-based distributions are included in a framework allowing the management of several ...

This paper presents a modified barebones particle swarm optimization OBPSO to solve constrained nonlinear optimization problems. The proposed approach OBPSO combines barebones particle swarm optimization BPSO and opposition-based learning OBL to improve the quality of solutions. A novel boundary search strategy is used to approach the boundary between the feasible and infeasible search region. ...

People who do not want immunizations represent a small fraction of the total population. However, they may have significant epidemiologic impact. Reasons for lack of support for immunization include ignorance, fear, contraindication, general opposition based on religion or philosophy, or "informed" opposition. The category of "informed" opposition includes those who have decided, based on relia...