This article proposes the Two-Phase Local Search for finding a good approximate set of non-dominated solutions. The two phases of this procedure are to (i) generate an initial solution by optimizing only one single objective, and then (ii) to start from this solution a search for non-dominated solutions exploiting a sequence of different formulations of the problem based on aggregations of the ...

In this paper a multi-objective nonlinear programming model of cellular manufacturing system is presented which minimize the intercell movements and maximize the sum of reliability of cells. We present a genetic approach for finding efficient solutions to the problem of cell formation for products having multiple routings. These methods find the non-dominated solutions and according to decision...

We present a class of theories of two dimensional gravity which admits homogeneous and isotropic solutions that are nonsingular and asymptotically approach a FRW matter dominated universe at late times. These models are generalizations of two dimensional dilaton gravity and both vacuum solutions and those including conformally coupled matter are investigated. In each case our construction leads...

Multi-objective evolutionary algorithms frequently use an archive of non-dominated solutions to approximate the Pareto front. We show that the truncation of this archive to a limited number of solutions can lead to oscillating and shrinking estimates of the Pareto front. New data structures to permit efficient query and update of the full archive are proposed, and the superior quality of fronta...

Based on the human-computer cooperation ideas, a Human-Computer Multi-Objective Cooperative Co-Evolutionary Method (HCMCCM) is developed to solve the complex engineering layout problem, in which the multiobjective optimization idea is integrated to avoid the "flooding" phenomenon that occurs during the combination of the artificial solutions and the algorithm solutions. In the proposed HCMCCM, ...

We examine the cosmological solutions of a tachyon field non minimally coupled to gravity through an effective Born-Infeld interacting Lagrangian with a power law potential, in order to investigate its equation of state as related to tracking properties. We find exact solutions in the case of a tachyon dominated universe and when the dominant component of the stress energy tensor is determined ...

In this paper, we propose a multiobjective Genetic Algorithm (mo-GA) for solving a multiobjective reliability optimization problem. In order to obtain high efficiency of searching non-dominated solutions, we combine the Improved Saving Pareto solutions Strategy (ISPS) and the adoptive Local Search (LS) with the multiobjective Genetic Algorithm. Through some numerical experiments, we evaluate th...

We present a new non-dominated sorting algorithm to generate the non-dominated fronts in multi-objective optimization with evolutionary algorithms, particularly the NSGA-II. The non-dominated sorting algorithm used by NSGA-II has a time complexity of O(MN(2)) in generating non-dominated fronts in one generation (iteration) for a population size N and M objective functions. Since generating non-...

Mixed-model assembly lines are increasingly accepted in many industrial environments to meet the growing trend of greater product variability, diversification of customer demands, and shorter life cycles. In this research, a new mathematical model is presented considering balancing a mixed-model U-line and human-related issues, simultaneously. The objective function consists of two separate com...

Semi-active fluid viscous dampers as a subset of control systems have shown their ability to reduce seismic responses of tall buildings. In this paper, multi-objective optimization of the performance of this group of dampers in reducing the seismic responses of buildings is studied using multi-objective genetic algorithms. For numerical example, two 7 and 18 stories buildings are chosen and mod...