Fuzzy clustering methods are conveniently employed in constructing a fuzzy model of a system, but they need to tune some parameters. In this research, FCM is chosen for fuzzy clustering. Parameters such as the number of clusters and the value of fuzzifier significantly influence the extent of generalization of the fuzzy model. These two parameters require tuning to reduce the overfitting in the...

in this study the performance and emissions characteristics of a heavy-duty, direct injection, compression ignition (ci) engine which is specialized in agriculture, have been investigated experimentally. for this aim, the influence of injection timing, load, engine speed on power, brake specific fuel consumption (bsfc), peak pressure (pp), nitrogen oxides (nox), carbon dioxide (co2), carbon mon...

in order to reduce both the weight of vehicles and the damage of occupants in a crash event simultaneously, it is necessary to perform a multi-objective optimization of the automotive energy absorbing components. in this paper, axial impact crushing behavior of the aluminum foam-filled thin-walled tubes are studied by the finite element method using commercial software abaqus. comparison of the...

In this paper, we present a multi-objective optimization approach for indoor wireless network planning subject to constraints for exposure minimization, coverage maximization and power consumption minimization. We consider heterogeneous networks consisting of WiFi Access Points (APs) and Long Term Evolution (LTE) femtocells. We propose a design framework based on Multi-objective Biogeography-ba...

A method called PAINT is introduced for computationally expensive multiobjective optimization problems. The method interpolates between a given set of Pareto optimal outcomes. The interpolation provided by the PAINT method implies a mixed integer linear surrogate problem for the original problem which can be optimized with any interactive method to make decisions concerning the original problem...

An approach to constructing a Pareto front approximation to computationally expensive multiobjective optimization problems is developed. The approximation is constructed as a sub-complex of a Delaunay triangulation of a finite set of Pareto optimal outcomes to the problem. The approach is based on the concept of inherent nondominance. Rules for checking the inherent nondominance of complexes ar...

In this paper, we propose a fine-grained grid-based multi-objective model which aims at optimizing base station antennas' configurations, such as transmit power, antenna tilt and antenna azimuth, in order to upgrading network performance in cellular networks. As the model is non-convex, non-smooth and discrete and computationally expensive, we use decomposition method to solve the MOP problem. ...

Evacuation route planning is one of the most crucial tasks for solving massive evacuation problem. In large public places, pedestrians should be transferred to safe areas when nature or man-made accidents happen. A multi-objective ant colony algorithm for massive pedestrian evacuation is presented in this paper. In the algorithm, three objectives, total evacuation time of all evacuees, total ro...

This paper looks at two variants of polynomial mutation used in various evolutionary optimisation algorithms for mutliobjective problems. The first is a non-highly disruptive and the second is a highly disruptive mutation. Both are used for problems with box constraints. A new hybrid polynomial mutation that combines the benefits of both is proposed and implemented. The experiments with three e...