Global changes of states are of crucial importance in optimization algorithms. We review some heuristic algorithms in which global updates are realized by a sort of real-space renormalization group transformation. Emphasis is on the relationship between the structure of low-energy excitations and “block-spins” appearing in the algorithms. We also discuss the implication of existence of a finite...

This paper presents an effective optimization method for nonlinear constrained optimization of retaining structures. A newly developed heuristic global optimization algorithm called gravitational search algorithm (GSA) is introduced and applied for the optimization of retaining structures. The optimization procedure controls all geotechnical and structural design constraints while reducing the ...

Grey wolf optimization (GWO) is one of the recently proposed heuristic algorithms imitating the leadership hierarchy and hunting mechanism of grey wolves in nature. The aim of these algorithms is to perform global optimization. This paper presents a modified GWO algorithm based on complex-valued encoding; namely the complex-valued encoding grey wolf optimization (CGWO). We use CGWO to test 16 u...

In order to improve the performance of basic bacterial foraging optimization (BFO) for various global optimization problems, a superior attraction bacterial foraging optimizer (SABFO) is proposed in this paper. In SABFO, a novel movement guiding technique termed as superior attraction strategy is introduced to make use of all bacteria historical experience as potential exemplars to lead individ...

logit models are one of the most important discrete choice models and they play an important role in describing decision makers’ choices among alternatives. in this paper the multi-nominal logit models has been used in mode choice modeling of isfahan. despite the availability of different mathematical computer programs there are not so many programs available for estimating discrete choice mode...

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. ...

Ant algorithm is a novel meta-heuristic optimization algorithm, but at the same time there are some disadvantages. This paper proposed an ant colony algorithm with route evaluation based on the basic ant colony algorithm. After all ant complete the route search once, the current search situation can be evaluated according to an improved formula of standard deviation, then to decide to update gl...

Many real life optimization problems are nonconvex and may have several local minima within their feasible region. Therefore, global search methods are needed. Metaheuristics are efficient global optimizers including a metastrategy that guides a heuristic search. Genetic algorithms, simulated annealing, tabu search and scatter search are the most well-know metaheuristics. In general, they do no...