Selecting an appropriate route for a given virtual circuit (VC) request in a virtual path based ATM network satisfying the required Quality of service (QoS) constraints is an important issue. Two of these important constraints are average network delay and reliability of the network. In this paper, a routing strategy based on Genetic Algorithm to find suboptimal routing solution for ATM network...

System reliability optimization is often faced with imprecise and conflicting goals such as reducing the cost of the system and improving the reliability of the system. The decision making process becomes fuzzy and multi-objective. In this paper, we formulate the problem as a fuzzy multi-objective nonlinear program (FMOOP). A fuzzy multiobjective genetic algorithm approach (FMGA) is proposed fo...

Multiobjective combinatorial optimization problems in various disciplines remain to be the focus of extensive research due to their inherent hard nature and difficulty of finding near-optimal solutions. Iterative heuristics like Tabu Search (TS) and Simulated Evolution (SimE) have successfully been employed to solve a range of such optimization problems [1]. These heuristics are able to obtain ...

This paper deals with multi-objective optimization in gait planning of a 7-dof biped robot ascending and descending some staircases. Both its power consumption as well as dynamic balance margin depends on a few common design parameters. The biped robot should have a maximum dynamic balance margin but at the expense of minimum power. Thus, a conflicting relationship exists between these two obje...

This study introduces an information granular-based fuzzy radial basis function neural networks (FRBFNN) based on multiobjective optimization and weighted least square (WLS). An improved multiobjective space search algorithm (IMSSA) is proposed to optimize the FRBFNN. In the design of FRBFNN, the premise part of the rules is constructed with the aid of Fuzzy C-Means (FCM) clustering while the c...

Abstract This study presents the modeling of multiobjective optimization problem in an intuitionistic fuzzy environment. The uncertain parameters are depicted as numbers, and crisp version is obtained using ranking function method. Also, we have developed a novel interactive neutrosophic programming approach to solve problems. proposed method involves neutral thoughts while making decisions. Fu...

The chapter aims to give computational algorithm to solve a multiobjective non-linear programming problem using Neutrosophic geometric programming technique. As the Neutrosophic optimization technique utilizes degrees of truth-membership, falsity-membership and indeterminacy-membership functions, we made a study of correspondence among those membership functions to see its impact on optimizatio...

Recently, a general-purpose local-search heuristic method called Extremal Optimization (EO) has been successfully applied to some NP-hard combinatorial optimization problems. This paper presents an investigation on EO with its application in multiobjective optimization and proposes a new novel elitist (1+ λ ) multiobjective algorithm, called Multiobjective Extremal Optimization (MOEO). In order...

This note presents the characterization of the stability set of the first kind for multiobjective nonlinear programming (MONLP) problems with fuzzy parameters either in the constraints or in the objective functions without any differentiability assumptions. These fuzzy parameters are characterized by triangular fuzzy numbers (TFNs). The existing results concerning the parametric space in convex...

In this paper, we propose a new multiobjective optimization approach based on the clonal selection principle. Our approach is compared with respect to other evolutionary multiobjective optimization techniques that are representative of the state-of-the-art in the area. In our study, several test functions and metrics commonly adopted in evolutionary multiobjective optimization are used. Our res...