This paper presents results of extensive computational experiments in which evolutionary multiobjective algorithms were used to find Pareto-optimal solutions to a complex structural design problem. In particular, Strength-Pareto Evolutionary Algorithm 2 (SPEA2) was combined with a mathematical programming method to find optimal designs of steel structural systems in tall buildings with respect ...

In this paper, the reliability formula of stress-strength model is derived for probability a component having strength X falling between two stresses T and Z, based on The New Weibull-Pareto Distribution with unknown parameter known common parameters . Four methods estimating are discussed which Maximum Likelihood, Method Moment, Least Square Weighted Method, comparison these estimations simula...

Evolutionary algorithms EA have proved to be well suited for optimization prob lems with multiple objectives Due to their inherent parallelism they are able to capture a number of solutions concurrently in a single run In this report we propose a new evolutionary approach to multicriteria optimization the Strength Pareto Evolutionary Algorithm SPEA It combines various features of previous multi...

In this paper, we focus on engineering Pareto-optimal digital circuits given the expected input/output behaviour with a minimal design effort. The design objectives to be minimised are: hardware area, response time and power consumption. We do so using the Strength Pareto Evolutionary Algorithms. This is novel application of multi-objective optimisation to circuit design. The performance and qu...

Owing to the incremental demands for electrical energy, distributed generation (DG) sources are becoming more important in distribution systems. Locations and capacities of DG sources have profoundly impacted on the system losses in a distribution network. In this paper, a novel Strength Pareto Evolutionary Algorithm (SPEA) is represented for optimal location and sizing of DG on distribution sy...

AbstractSingleand multicriteria evolution strategies are implemented to optimize micro-fluidic devices, namely the shape of a microchannel used for bioanalysis and the mixing rate in a micromixer used for medical applications. First, multimembered evolution strategies employing mutative step size adaptation are combined with the Strength Pareto Approach. In order to support targetting, an exten...

The Bus Driver Rostering Problem (DRP) consists of assigning bus drivers to daily duties during a planning period. The problem considers hard constraints imposed by institutional and legal requirements. Solutions should as much as possible satisfy soft constraints that qualify rosters according to either the company’s or the drivers’ interests. A bi-objective version of the DRP is considered an...

This paper presents a new approach to handle constrained optimization using evolutionary algorithms. The new technique converts constrained optimization to a two-objective optimization: one is the original objective function, the other is the degree function violating the constraints. By using Paretodominance in the multi-objective optimization, individual's Pareto strength is defined. Based on...

This paper presents a new multiobjective evolutionary algorithm for Environmental/Economic power Dispatch (EED) problem. The EED problem is formulated as a nonlinear constrained multiobjective optimization problem. A new Strength Pareto Evolutionary Algorithm (SPEA) based approach is proposed to handle the problem as a true multiobjective problem with competing and non-commensurable objectives....

The Pareto-based approaches have shown some success in designing multiobjective evolutionary algorithms. Their methods of fitness assignment are mainly from the information of dominated and nondominated individuals. On the top of the hierarchy of multiobjective evolutionary algorithms, the Strength Pareto Evolutionary Algorithm (SPEA) has been elaborately designed with this principle in mind. I...