In this paper, a new reactive power market clearing (RPMC) mechanism for day-ahead competitive electricity market is developed based on multi-objective optimization approach. In proposed mechanism, three objective functions such as total payment function (TPF) for reactive power support from generators and synchronous condensers, total real transmission loss (TRTL) and voltage stability enhance...

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 the paper, a novel stochastic Multi-Objective Self-Organizing Migrating Algorithm (MOSOMA) is introduced. For the search of optima, MOSOMA employs a migration technique used in a single-objective Self Organizing Migrating Algorithm (SOMA). In order to obtain a uniform distribution of Pareto optimal solutions, a novel technique considering Euclidian distances among solutions is introduced. MO...

The nondominated sorting genetic algorithm with elitism (NSGA-II) is widely used due to its good performance on solving multiobjective optimization problems. In each iteration of NSGA-II, truncation selection is performed based on the rank and crowding distance of each solution. There are, however, drawbacks in this process. These drawbacks to some extent cause overlapping solutions in the popu...

This paper presented a parallel hybrid electric vehicle (HEV) equipped with a hybrid energy storage system. To handle complex energy flow in the powertrain system of this HEV, a fuzzy-based energy management strategy was established. A chaotic multi-objective genetic algorithm, which optimizes the parameters of fuzzy membership functions, was also proposed to improve fuel economy and HC, CO, an...

A multiobjective optimization problem which focuses on parallel machines scheduling is considered. This problem consists of scheduling n independent jobs onm identical parallel machines with release dates, due dates, and sequence-dependent setup times. The preemption of jobs is forbidden. The aim is to minimize two different objectives: makespan and total tardiness. The contribution of this pap...

Multiobjective evolutionary algorithms (EAs) that use nondominated sorting and sharing have been criticized mainly for their: 1) ( ) computational complexity (where is the number of objectives and is the population size); 2) nonelitism approach; and 3) the need for specifying a sharing parameter. In this paper, we suggest a nondominated sorting-based multiobjective EA (MOEA), called nondominate...

In this paper, we present a novel multi-objective mathematical model for capacitated single allocation hub location problem. There are the vehicle capacity constraint and capacity restrictions amount of the incoming flow to the hub while the balancing requirements of incoming quantities of flow to the each hub is considered. Moreover, there is a set of available capacities for each potential hu...