The problem of Scheduling Hot Rolling Pass of Steels is very complex because it has large spaces search for solutions. The aim of this work was the Multi-Objective Optimization (MOO) of hot rolling steel sheets in a finishing train of six steps, implementing the second generation of Nondominated Sorting Genetic Algorithm (NSGA-II). It was used two different crossover (AG1 y AG2) operators and t...

Controllers design problems are multi objective optimization problems as the controller must satisfy several performance measures that are often conflicting and competing with each other. In multi-objective approach a set of solutions can be generated from which the designer can select a final solution according to his requirement and need. This paper presents the design and analysis Proportion...

The crossover operator has always been regarded as the primary search operator in genetic algorithm (GA) because it exploits the available information from the population about the search space. Moreover, it is one of the components to consider for improving the behavior of the GA. To improve performance of GA multi parent crossover operators have been used. Multi parent crossover operators inv...

Voltage stability has become an important issue in planning and operation of many power systems. Contingencies such as unexpected line outages in a stressed system may often result in voltage instability, which may lead to voltage collapse. This paper presents evolutionary algorithm techniques like Genetic Algorithm (GA) and Non-dominated Sorting Genetic Algorithm II (NSGA II) approach for solv...

The huge demand for real time services in wireless mesh networks (WMN) creates many challenging issues for providing quality of service (QoS). Designing of QoS routing protocols, which optimize the multiple objectives is computationally intractable. This paper proposes a new model for routing in WMN by using Modified Non-dominated Sorting Genetic Algorithm-II (MNSGA-II). The objectives which ar...

Test Case Selection (TCS) aims to select a subset of the test suite run for regression testing. The selection is typically based on past coverage and execution cost data. Researchers have successfully used multi-objective evolutionary algorithms (MOEAs), such as NSGA-II its variants, solve this problem. These MOEAs use traditional crossover operators create new candidate solutions through genet...

Abstract This paper proposes the Self-Adaptive algorithm for Multi-Objective Constrained Optimization by using Radial Basis Function Approximations, SAMO-COBRA. automatically determines best Function-fit as surrogates objectives well constraints, to find new feasible Pareto-optimal solutions. SAMO-COBRA is compared a wide set of other state-of-the-art algorithms (IC-SA-NSGA-II, SA-NSGA-II, NSGA...

time-dependent vehicle routing problem is one of the most applicable but least-studied variants of routing and scheduling problems. in this paper, a novel mathematical formulation of time-dependent vehicle routing problems with heterogeneous fleet, hard time widows and multiple depots, is proposed. to deal with the traffic congestions, we also considered that the vehicles are not forced to come...

Trajectory planning is always a hot issue for harvesting manipulator in practice considering that the limitations of mechanical structure and other nonlinear factors lead to long harvest time, big jerk high energy consumption. The cubic spline algorithm, fifth-order polynomial interpolation fusing algorithm are used shorten reduce enhance robustness manipulator, respectively. Then trajectory pr...

Reglero. This work will never be produced without kindly help and assistance of professors Francisco Herrera and Antonio Gonzáles. And I am gratefull to Rocio Romero for providing me NSGA II description.