Multiobjective Pareto optimal solutions for epoxy semi-batch polymerization process are obtained by adapting nondominated sorting genetic algorithm II (NSGA II). The objective is to produce polymer of maximum possible number average molecular weight (Mn) with a specified value of polydispersity index (PDI) and number average molecular weight in minimum possible time. The M and reaction time a p...

In this paper we present a study of the application of Evolutionary Computation methods to the optimisation of the start-up of a combined cycle power plant. We propose a multiobjective approach considering different objectives for the optimisation in order to reduce the pollution emissions and to maximise the efficiency of the plant. We compare a multiobjective evolutionary algorithm (NSGA-II) ...

Antenna design problems often require the optimization of several conflicting objectives such as gain maximization, sidelobe level (SLL) reduction and input impedance matching. Multiobjective Evolutionary Algorithms (MOEAs) are suitable optimization techniques for solving such problems. An efficient algorithm is Generalized Differential Evolution (GDE3), which is a multi-objective extension of ...

One way to cope with a huge design space formed by several parameters is using methods for Automatic Design Space Exploration (ADSE). Recently we developed a Framework for Automatic Design Space Explorations focused on micro-architectural optimizations. In this article we evaluate the influence of three different evolutionary algorithms on the performance of design space explorations. More prec...

In this paper, a new genetic algorithm for multi-objective optimization problems is introduced. That is called ”Neighborhood Cultivation GA (NCGA)”. In the recent studies such as SPEA2 or NSGA-II, it is demonstrated that some mechanisms are important; the mechanisms of placement in an archive of the excellent solutions, sharing without parameters, assign of fitness, selection and reflection the...

In this paper, a simple but efficient Non-dominated Sorting Genetic Algorithm (NSGA) II based technique is proposed for optimizing the Degree of Hybridization (DOH) in parallel passenger hybrid cars. The authors’ objective is to improve performance, maximize fuel economy and at the same time, minimize mass and emissions as much as possible, by optimal selection of DOH. The NSGA-II, which is a m...

The growing importance of electric distribution systems justifies new investments in their expansion and evolution. It is well known in the literature that optimization techniques can provide better allocation of the financial resources available for such a task, reducing total installation costs and power losses. In this work, the NSGA-II algorithm is used for obtaining a set of efficient solu...

Finding an optimal solution for QoS-aware Web service composition with various restrictions on qualities is a multi-objective optimisation problem. A popular multi-objective genetic algorithm, NSGA-II, is studied in order to provide a set of optimal solutions for QoS-based service composition. Experiments with different numbers of abstract and concrete services confirm the expected behaviour of...

The following paper describes a cooperative coevolutionary algorithm which incorporates a novel collaboration formation mechanism. It encourages rewarding of components participating in successful collaborations from each sub-population. The successfulness of the collaboration is measured by a non-dominated sorting procedure. The algorithm has demonstrated it can perform comparably with the NSG...

Low specific speed centrifugal pumps (LSSCP) are widely utilized in district energy systems to promote the integration of renewable energy. However, performance LSSCP becomes inefficient due harsh operating conditions resulting substantial increase consumption. Many-objective optimization is significant improving and promoting sustainability systems. Among existing methods, global methods limit...