Many practically relevant problems have several objectives to be maximized or minimized, taking us into the area of Multiple Objective Optimization (MOO). In multi-objective optimization several conflicting objectives have to be simultaneously optimized. Therefore, there is usually no single solution which would give the best values for all the objective functions considered by the decision mak...

With the increasing demand for high quality, more efficient and less area circuits, the problem of circuit design has become a multi-objective optimization problem. Therefore, there should evolve new methodologies for designing logic circuits. The new paradigm is expected to radically change the synthesis procedures in a way that can help discovering novel designs and/or more efficient circuits...

Ant Colony Optimization (ACO) algorithm is a novel metaheuristic algorithm that has been widely used for different combinational optimization problem and inspired by the foraging behavior of real ant colonies. Ant Colony Optimization has strong robustness and easy to combine with other methods in optimization. In this paper, an efficient ant colony optimization algorithm with uniform mutation o...

the capacitated clustering problem (ccp) is one of the most importantcombinational optimization problems that nowadays has many real applications inindustrial and service problems. in the ccp, a given n nodes with known demandsmust be partitioned into k distinct clusters in which each cluster is detailed by anode acting as a cluster center of this cluster. the objective is to minimize the sumof...

Many practically relevant problems have several objectives to be maximized or minimized, taking us into the area of Multiple Objective Optimization (MOO). In multi-objective optimization several conflicting objectives have to be simultaneously optimized. Therefore, there is usually no single solution which would give the best values for all the objective functions considered by the decision mak...

With the increasing demand for high quality, more efficient and less area circuits, the problem of logic circuit design has become a multiobjective optimization problem. In this paper, a multiobjective optimization of logic circuits based on a fuzzified Ant Colony (ACO) algorithm is presented. The results obtained using the proposed algorithm are compared to those obtained using SIS in terms of...

The application of stochastic methods in engineering research and optimization has been increasing over the past few decades. Ant Colony Optimization, in particular, has been attracting growing attention as a promising approach both in discrete and continuous domains. The present work proposes a multiobjective Ant Colony Optimization for continuous domains showing good convergence properties an...

Nowadays, Wireless network becomes unavoidable resource in the modern world. Security of wireless network becomes very important critical research issue in this decade. This paper focused on various kinds of attacks and proposed methodology for authentication. Attacks which may be passive attacks or active attacks will collapse the entire operation of the whole network. The attacks on wireless ...

Ant colony algorithm, a heuristic simulated algorithm, provides better solutions for non-convex, non-linear and discontinuous optimization problems. For ant colony algorithm, it is frequently to be trapped into local optimum, which might lead to stagnation. This article presents the city-select strategy, local pheromone update strategy, optimum solution prediction strategy and local optimizatio...