In this paper, quasi-oppositional teaching-learning based optimization (QOTLBO) is introduced and successfully applied …). The main drawback of the original teaching-learning based optimization (TLBO) is that it gives a local optimal solution …-based optimization (HDE-BBO). This method gives better solution quality in finding the optimal parameter settings for FACTS devices to …

In solving certain optimization problems, the corresponding Lagrangian dual problem is often solved simply because in …. Another interesting aspect of dual problems is that both lower and upper-level optimization problems involve only box … constraints and no other equality of inequality constraints. In this paper, we propose a coevolutionary dual optimization (CEDO …

Genetic algorithms are a class of probabilistic optimization techniques that have proved useful in a wide variety of …

locations, and wind direction. Since the turbine layout design is a constrained optimization problem, for ease of solving it … is developed to solve the transformed bi-criteria optimization problem, which maximizes the expected energy output, as …

. This paper introduces a new combined optimization approach, which adjusts the BHE positions as well as the individually … changing load profile. The optimization of only the BHE positions without optimizing the individual BHE loads nearly produces … the same improvement of the underground temperature change of approximately 12% as an optimization of the BHE loads …

have attracted much attention and wide applications in a variety of fields, especially for optimization and design. EAs …-world optimization applications. The potentialities of DE are its simple structure, easy use, convergence speed and robustness. To … improve the global optimization property of DE, in this paper, a DE approach based on measure of population's diversity and …