With the increasing rate of population in big cities around world, tendency to build new buildings suburb main or large apartments has been highlighted. In this regard, building residential complexes seen a dramatic increase these areas as it makes possible number units within reasonable space. Although have brought numerous benefits, they are some challenges regarding their construction proces...

Many real-world problems are dynamic, requiring an optimization algorithm which is able to continuously track a changing optimum over time. In this paper, we present new variants of Particle Swarm Optimization (PSO) specifically designed to work well in dynamic environments. The main idea is to extend the single population PSO and Charged Particle Swarm Optimization (CPSO) methods by constructi...

One of the most important applications of multi-objective optimization is adjusting parameters ofpractical engineering problems in order to produce a more desirable outcome. In this paper, the decoupled sliding mode control technique (DSMC) is employed to stabilize an inverted pendulum which is a classic example of inherently unstable systems. Furthermore, a new Multi-Objective Particle Swarm O...

The scarcity of water resources nowadays lays stress on researchers to develop strategies aiming at making the best benefit currently available resources. One these is ensuring that reliable and near-optimum designs distribution systems (WDSs) are achieved. Designing WDSs a discrete combinatorial NP-hard optimization problem, its complexity increases when more objectives added. Among many exist...

This paper proposes a hybrid particle swarm approach called Simple Multi-Objective Particle Swarm Optimizer (SMOPSO) which incorporates Pareto dominance, an elitist policy, and two techniques to maintain diversity: a mutation operator and a grid which is used as a geographical location over objective function space. In order to validate our approach we use three well-known test functions propos...