In recent years, web services technology is becoming increasingly popular because of the convenience, low cost and capacity to be composed into high-level business processes. The service location-allocation problem for a web service provider is critical and urgent, because some factors such as network latency can make serious effect on the quality of service (QoS). This paper presents a multi-o...

This paper proposes an extension of the Gravitational Search Algorithm (GSA) to multi-objective optimization problems. The new algorithm, called Non-dominated Sorting GSA (NSGSA), utilizes the non-dominated sorting concept to update the gravitational acceleration of the particles. An external archive is also used to store the Pareto optimal solutions and to provide some elitism. It also guides ...

This paper proposes a Stochastic Chance-Constrained Programming Model (SCCPM) for the supplier selection problem to select best suppliers offering incremental volume discounts in a conflicting multi-objective scenario and under the event of uncertainty. A Fast Non-dominated Sorting Genetic Algorithm (NSGA-II), a variant of GA, adept at solving Multi Objective Optimization, is used to obtain the...

This paper presents an evolutionary algorithm based technique to solve multi-objective feature subset selection problem. The data used for classification contains large number of features called attributes. Some of these attributes are not relevant and needs to be eliminated. In classification procedure, each feature has an effect on the accuracy, cost and learning time of the classifier. So, t...

The non-dominated sorting algorithm by Jensen, generalized by Fortin et al to handle the cases of equal objective values, has the running time complexity of O(N logK−1 N) in the general case. Here N is the number of points, K is the number of objectives and K is thought to be a constant when N varies. However, the complexity was not proven to be the same in the worst case. A slightly modified v...

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,...

This paper presents the application of Nondominated Sorting Genetic Algorithm II (NSGA II) in solving multiple-objective signal timing optimization problem (MOSTOP). Some recent researches on intersection signal timing design optimization and multi-objective evolutionary algorithms are summarized. NSGA II, which can find more of the Pareto Frontiers and maintain the diversity of the population,...

A multi-objective vehicle path planning method has been proposed to optimize path length, path safety and path smoothness using the elitist non-dominated sorting genetic algorithm (NSGA-II). Four different path representation schemes that begin its coding from the start point and move one grid at a time towards the destination point are proposed. Minimization of traveled distance, maximization ...