The stress – strength model is one of the models that are used to compute reliability. In this paper, we derived mathematical formulas for reliability follows Rayleigh Pareto (Rayl. Par) distribution. Here, has a single component, where Y subjected X, represented by moment, function, restricted behavior, and ordering statistics. Some estimation methods were used, which maximum likelihood, ordin...

The most important issue in multi-objective optimization problems is to determine the Pareto points along the Pareto frontier. If the optimization problem involves multiple conflicting objectives, the results obtained from the Pareto-optimality will have the trade-off solutions that shaping the Pareto frontier. Each of these solutions lies at the boundary of the Pareto frontier, such that the i...

A new software tool making use of a genetic algorithm for multi-objective experimental optimization (GAME.opt) was developed based on a strength Pareto evolutionary algorithm. The software deals with high dimensional variable spaces and unknown interactions of design variables. This approach was evaluated by means of multi-objective test problems replacing the experimental results. A default pa...

We consider a multi-location inventory system where inventory choices at each location are centrally coordinated. Lateral Transshipments are allowed as recourse actions within the same echelon in the inventory system to reduce costs and improve service level. However this transshipment process usually causes undesirable lead times. In this paper, we propose a multiobjective model of the multi-l...

A multi-objective optimization approach for fibrous composite plates with curvilinear fibers is proposed in the present study. The non-dominated sorting genetic algorithm (NSGA-II) is used to obtain Pareto-optimum solutions, where the presence of a trade-off relation between the mechanical performance and curvatures of reinforcing fibers has been established. The in-plane strength around a circ...

This paper presents a new approach to treat reactive power (VAr) planning problem using multi-objective evolutionary algorithms. Specifically, Strength Pareto Evolutionary Algorithm (SPEA) and Multi-Objective Particle Swarm Optimization (MOPSO) approaches have been developed and successfully applied. The overall problem is formulated as a nonlinear constrained multi-objective optimization probl...

A sampling design method that seeks chlorine sampling locations using a multiobjective optimization framework is proposed here. The design problem is formulated as a threeand two-objective optimization where the parameter estimation accuracy (F1) is maximized, the the number of sensors is minimized (F2) and the weighted nodal sensitivity is maximized (F3). Trade-off curves are generated using t...