Design optimization of structures with discrete and continuous search spaces is a complex optimization problem with lots of local optima. Metaheuristic optimization algorithms, due to not requiring gradient information of the objective function, are efficient tools for solving these problems at a reasonable computational time. In this paper, the Doppler Effect-Mean Euclidian Distance Threshold ...

In this paper a league championship algorithm (LCA) is developed for structural optimization where the optimization variables are of discrete type and the set of the values possibly obtained by each variable is also given. LCA is a relatively new metaheuristic algorithm inspired from sport championship process. In LCA, each individual can choose to approach to or retreat from other individuals ...

When musicians compose the harmony, they usually try various possible combinations of the music pitches stored in their memory, which can be considered as a optimization process of adjusting the input (pitches) to obtain the optimal output (perfect harmony). Harmony search draws the inspiration from harmony improvisation, and has gained considerable results in the field of optimization, althoug...

The paper describes software combining parametric geometric modeling with a version of the harmony search method, modified to support multimodal structural optimization. Researchers have recognized the potential of population-based optimization methods, such as genetic algorithms, to support multimodal optimization: that is, generating a diverse range of good alternative solutions, rather than ...

This paper introduces a Travel Demand Management (TDM) model in order to decrease the transportation externalities by affecting on passengers’travel choices. Thus, a bi-objective bi-modal optimization model for road pricing is developed aiming to enhance environmental and social sustainability by considering to minimize the air pollution and maximize the social welfare as its objectives. This m...

ant colony optimisation (aco) algorithm and adaptive refinement mechanism are used in this paper for solution of optimization problems. many of the real engineering problems are، however، of continuous nature and finding their solution by discrete ant based algorithms requires discretisation of the decision variables in which affected the convergence and performance of the algorithm. in this pa...

Naturally occurring phenomenon serves as an unbiased guide for solving various optimization problems. This paper compiles some of the population-based, stochastic optimization algorithms including the recently developed social impact theory based optimizer, SITO. The current state of research, including the natural phenomena followed by each and some of their applications to solve various optim...

This paper discusses the optimal node placement problem of Industrial Wireless Sensor Networks (IWSNs). Compared with the non-industrial Wireless Sensor Networks (WSNs), IWSNs have a critical requirement on the reliability of networks. Thus, a new model of the IWSNs node placement is formulated in which the reliability, cost, load constraint and scalability are taken into account. Considering i...

The main aim of the project is to develop a new efficient optimization method, called „Teaching–Learning-Based Optimization (TLBO)‟, for the optimization of mechanical design problems. The process of TLBO is divided into two parts. The first part consists of the „Teacher Phase‟ and the second part consists of the „Learner Phase‟. „Teacher Phase‟ means learning from the teacher and „Learner Phas...