this paper proposes a bi-objective model for the facility location problem under a congestion system. the idea of the model is motivated by applications of locating servers in bank automated teller machines (atms), communication networks, and so on. this model can be specifically considered for situations in which fixed service facilities are congested by stochastic demand within queueing frame...

A multi-objective genetic algorithm is introduced to predict the assignment of protein solid-state NMR (SSNMR) spectra with partial resonance overlap and missing peaks due to broad linewidths, molecular motion, and low sensitivity. This non-dominated sorting genetic algorithm II (NSGA-II) aims to identify all possible assignments that are consistent with the spectra and to compare the relative ...

This paper demonstrates that the self-adaptive technique of Differential Evolution (DE) can be simply used for solving a multiobjective optimization problem where parameters are interdependent. The real-coded crossover and mutation rates within the NSGA-II have been replaced with a simple Differential Evolution scheme, and results are reported on a rotated problem which has presented difficulti...

Fractional-order proportional-integral-derivative (FOPID) controllers are designed for load-frequency control (LFC) of two interconnected power systems. Conflicting time-domain design objectives are considered in a multi-objective optimization (MOO)-based design framework to design the gains and the fractional differ-integral orders of the FOPID controllers in the two areas. Here, we explore th...

In this paper a hybrid parallel multi-objective genetic algorithm is proposed for solving 0/1 knapsack problem. Multiobjective problems with non-convex and discrete Pareto front can take enormous computation time to converge to the true Pareto front. Hence, the classical multi-objective genetic algorithms (MOGAs) (i.e., nonParallel MOGAs) may fail to solve such intractable problem in a reasonab...

In real world most of the optimization problems are multi-objective in nature. These problems take large amount of time to congregate to the true Pareto front. So the basic algorithm like non parallel NSGA II may not able to solve such problem in ?-tolerable amount of time. This paper proposes a new hybrid parallel multi-objective genetic algorithm and solve one of the real life problem i. e. ,...

In this paper, a Non-dominated Sorting Genetic Algorithm-II (NSGA-II) based approach is presented for distribution system reconfiguration. In contrast to the conventional GA based methods, the proposed approach does not require weighting factors for conversion of multi-objective function into an equivalent single objective function. In order to illustrate the performance of the proposed method,...

In this paper, we present an optimal burn-in model for repairable assembly products (RAP) sold under warranty. The general repairable products, sold under warranty and optimal burn-in model by Sheu (2004) are further extended to the case in which the probability of type II failure is independent for a parent item. This paper investigates a parent item (product or system) made up of two items (s...

In this paper, we study different methods of solving joint redundancy-availability optimization for series-parallel systems with multi-state components. We analyzed various effective factors on system availability in order to determine the optimum number and version of components in each sub-system and consider the effects of improving failure rates of each component in each sub-system and impr...

This paper proposes a new fuzzy assessing procedure with application in management decision making. The proposed fuzzy approach build the membership functions for system characteristics of a standby repairable system. This method is used to extract a family of conventional crisp intervals from the fuzzy repairable system for the desired system characteristics. This can be determined with a set ...