in this work, harmony search meta-heuristic optimization algorithm has been developed for aerodynamic shape optimization problem for the first time. the aerodynamic shape, which has been investigated, is an airfoil with parces method for its shape parameterization. the problem was minimization of aerodynamic objective function using inverse design method and the objective function has been the ...

nowadays, software cost estimation (sce) with machine learning techniques are more performance than other traditional techniques which were based on algorithmic techniques. in this paper, we present a new hybrid model of multi-layer perceptron (mlp) artificial neural network (ann) and ant colony optimization (aco) algorithm for high accuracy in sce called multilayer perceptron ant colony optimi...

augmented downhill simplex method (adsm) is introduced here, that is a heuristic combination of downhill simplex method (dsm) with random search algorithm. in fact, dsm is an interpretable nonlinear local optimization method. however, it is a local exploitation algorithm; so, it can be trapped in a local minimum. in contrast, random search is a global exploration, but less efficient. here, rand...

in recent years, significant research efforts have been devoted to the optimal planning of power systems. substation expansion planning (sep) as a sub-system of power system planning consists of finding the most economical solution with the optimal location and size of future substations and/or feeders to meet the future demand. the large number of design variables, and combination of discrete ...

in this paper, the problem of layout optimization for x-bracing of steel frames is studied using the ant system (as). a new design method is employed to share the gravity and the lateral loads between the main frame and the bracings according to the requirements of the ibc2006 code. an algorithm is developed which is called optimum steel designer (osd). an optimization method based on an approx...

Meta-heuristic algorithms are applied in optimization problems in a variety of fields, including engineering, economics, and computer science. In this paper, seven population-based meta-heuristic algorithms are employed for size and geometry optimization of truss structures. These algorithms consist of the Artificial Bee Colony algorithm, Cyclical Parthenogenesis Algorithm, Cuckoo Search algori...

The minimum crossing number problem is among the oldest and most fundamental problems arising in the area of automatic graph drawing. In this paper, eight population-based meta-heuristic algorithms are utilized to tackle the minimum crossing number problem for two special types of graphs, namely complete graphs and complete bipartite graphs. A 2-page book drawing representation is employed for ...

Foreign exchange rate prediction is a stimulating research area from past decade. There are several statistical and machine learning methods already have been proposed by the researchers for foreign exchange rate prediction which provide better results. These models performed a vital role in future financial decision making which is taken by financial department administration of that country a...

the traveling salesman problem (tsp) is the problem of finding the shortest tour through all the nodes that a salesman has to visit. the tsp is probably the most famous and extensively studied problem in the field of combinatorial optimization. because this problem is an np-hard problem, practical large-scale instances cannot be solved by exact algorithms within acceptable computational times. ...

Selecting approaches with appropriate accuracy and suitable speed for the purpose of making decision is one of the managers’ challenges. Also investing decision is one of the main decisions of managers and it can be referred to securities transaction in financial markets which is one of the investments approaches. When some assets and barriers of real world have been considered, optimization of...