We present a multi-objective evolutionary algorithm to exploit a medium-sized fuzzy outranking relation to derive a partial order of classes of alternatives (we call it RP-NSGA-II). To measure the performance of RP-NSGA-II, we present an empirical study over a set of simulated multi-criteria ranking problems. The result of this study shows that RP-NSGA-II can effectively exploit a medium-sized ...

Particle Swarm Optimization (PSO) has received increased attention in the optimization research community since its first appearance. Regarding multi-objective optimization, a considerable number of algorithms based on Multi-Objective Particle Swarm Optimizers (MOPSOs) can be found in the specialized literature. Unfortunately, no experimental comparisons have been made in order to clarify which...

This paper presents an application of an evolutionary optimization algorithm for multiobjective analysis of selective withdrawal from a thermally stratified reservoir. A multiobjective particle swarm optimization (MOPSO) algorithm is used to find nondominated (Pareto) solutions when minimizing deviations from outflow water quality targets of: (i) temperature; (ii) dissolved oxygen (DO); (iii) t...

In this paper, considering multiple interference regions simultaneously, an optimal antenna deployment problem for distributed Multi-Input Multi-Output (MIMO) radar is investigated. The optimal antenna deployment problem is solved by proposing an antenna deployment method based on MultiObjective Particle Swarm Optimization (MOPSO). Firstly, we construct a multi-objective optimization problem fo...

A data-driven approach for the optimization of a heating, ventilation, and air conditioning (HVAC) system in an office building is presented. A neural network (NN) algorithm is used to build a predictive model since it outperformed five other algorithms investigated in this paper. The NN-derived predictive model is then optimized with a strength multi-objective particle-swarm optimization (S-MO...

The automotive deployment problem is a real-world constrained multiobjective assignment problem in which software components must be allocated to processing units distributed around a car’s chassis. Prior work has shown that evolutionary algorithms such as NSGA-II can produce good quality solutions to this problem. This paper presents a population-based ant colony optimisation (PACO) approach t...

Portfolio optimization is a serious challenge for financial engineering and has pulled down special attention among investors. It has two objectives: to maximize the reward that is calculated by expected return and to minimize the risk. Variance has been considered as a risk measure. There are many constraints in the world that ultimately lead to a non–convex search space such as cardinality co...

numerous problems encountered in real life cannot be actually formulated as a single objective problem; hence the requirement of multi-objective optimization (moo) had arisen several years ago. due to the complexities in such type of problems powerful heuristic techniques were needed, which has been strongly satisfied by swarm intelligence (si) techniques. particle swarm optimization (pso) has ...

Abstract Nowadays, fog computing as a complementary facility of cloud has attracted great attentions in research communities because it extraordinary potential to provide resources and processing services requested for applications at the edge network near users. Recent researchers focus on how efficiently engage networks capabilities execution supporting IoT associated requirement. However, in...

Due to the increased levels of uncertainty in world today and expansion supply chain boundaries, companies have been observed trying enhance resilience deal with disruptions caused by severe disasters. There is, however, a new stimulus for disorder, something quite similar what has witnessed recently. It is phenomenon called pandemics such as SARS, Ebola, Coronaviruses. On other hand, result im...