An Efficient Metaheuristic Algorithm for Engineering Optimization: SOPT

Metaheuristic algorithms are well-known optimization tools which have been employed for solving a wide range of optimization problems so far. In the present study, a simple optimization (SOPT) algorithm with two main steps; namely exploration and exploitation, is provided for practical applications. Aside from a reasonable rate of convergence attained, the ease in its implementation and dependency on few parameters only are among the advantageous characteristics of the proposed SOPT algorithm. The efficiency of the developed algorithm is investigated through engineering design optimization problems and the results are reported. The comparison of the numerical results with those of other metaheuristic techniques demonstrates the promising performance of the algorithm as a robust optimization tool for practical purposes.
International Journal of Optimization in Civil Engineering


Performance evaluation of metaheuristic search techniques in the optimum design of real size pin jointed structures
Hasançebi, Oğuzhan; Dogan, E.; Erdal, F.; Saka, M. P. (2009-03-01)
In recent years a number of metaheuristic search techniques have been widely used in developing structural optimization algorithms. Amongst these techniques are genetic algorithms, simulated annealing, evolution strategies, particle swarm optimizer, tabu search, ant colony optimization and harmony search. The primary goal of this paper is to objectively evaluate the performance of abovementioned seven techniques in optimum design of pin jointed structures. First, a verification of the algorithms used to imp...
Optimum Design of Geodesic Steel Domes Under Code Provisions using Metaheuristic Techniques
Hasançebi, Oğuzhan; Saka, Mehmet Polat (2010-06-01)
Metaheuristic search techniques strongly employ randomized decisions while searching for solutions to structural optimization problems. These techniques play an increasingly important role for practically solving hard combinatorial problems from various domains. Over the past few years there has been considerable success in developing metaheuristic search algorithms as well as randomized systematic search methods for obtaining solutions to discrete programming problems. This paper examines minimum weight de...
Evaluating Efficiency of Big-Bang Big-Crunch in Benchmark Engineering Optimization Problems
Hasançebi, Oğuzhan; Erol, Osman Kaan (2011-06-01)
Engineering optimization needs easy-to-use and efficient optimization tools that can be employed for practical purposes. In this context, stochastic search techniques have good reputation and wide acceptability as being powerful tools for solving complex engineering optimization problems. However, increased complexity of some metaheuristic algorithms sometimes makes it difficult for engineers to utilize such techniques in their applications. Big-Bang Big-Crunch (BB-BC) algorithm is a simple metaheuristic op...
Novel multiobjective TLBO algorithms for the feature subset selection problem
Kiziloz, Hakan Ezgi; Deniz, Ayca; Dokeroglu, Tansel; Coşar, Ahmet (2018-09-06)
Teaching Learning Based Optimization (TLBO) is a new metaheuristic that has been successfully applied to several intractable optimization problems in recent years. In this study, we propose a set of novel multiobjective TLBO algorithms combined with supervised machine learning techniques for the solution of Feature Subset Selection (FSS) in Binary Classification Problems (FSS-BCP). Selecting the minimum number of features while not compromising the accuracy of the results in FSS-BCP is a multiobjective opti...
Optimum design of steel frames using stochastic search techniques based on natural phenomena: A review
Saka, M. P. (2007-09-21)
Recent developments in optimization techniques that deal with finding the solution of combinatorial optimization problems has provided steel designers with new capabilities. These new optimization techniques use nature as a source of inspiration to develop new procedures for solving complex engineering problems. Among these, evolutionary algorithms mimic evolutionary biology and make use of the principle of the survival of the fittest to establish a numerical search algorithm. In the immune system algorithm...
Citation Formats
O. Hasançebi, “An Efficient Metaheuristic Algorithm for Engineering Optimization: SOPT,” International Journal of Optimization in Civil Engineering, pp. 477–489, 2012, Accessed: 00, 2021. [Online]. Available: