Darwinian evolution is intrinsically a robust search and optimization mechanism. Living organisms demonstrate optimized complex behavior at every level: the cell, the organ, the individual, and the population. The problems that biological species have solved are typified by chaos, chance, temporality, and nonlinear inter-activities. These are also characteristics of problems that have proved to...

Often, in many engineering applications it is required to find the best approximate solution of multi-objective optimization problems quick and with good accuracy. Multi-objective optimization problems are very common and important in real world applications, and as such many researchers are still working to devise various novel heuristic and mathematical approaches for their solution. Mathemat...

Given a heuristic estimate of the relative safety of a hybrid dynamical system trajectory, we transform the initial safety problem for dynamical systems into a global optimization problem. We compare untuned performance of several Simulated Annealing and Multi Level Single Linkage method variants, and discuss the dynamic use of knowledge gained during optimization.

The number of heuristic optimization algorithms has exploded over the last decade with new methods being proposed constantly. A recent overview of existing heuristic methods has listed over 130 algorithms. The majority of these optimization algorithms have been designed and applied to solve real-parameter function optimization problems, each claiming to be superior to other methods in terms of ...

The main aim of the present study is to achieve optimum design of reinforced concrete (RC) plane moment frames using bat algorithm (BA) which is a newly developed meta-heuristic optimization algorithm based on the echolocation behaviour of bats. The objective function is the total cost of the frame and the design constraints are checked during the optimization process based on ACI 318-08 code. ...