this article presents the application of two algorithms: heuristic big bang-big crunch (hbb-bc) and a heuristic particle swarm ant colony optimization (hpsaco) to discrete optimization of reinforced concrete planar frames subject to combinations of gravity and lateral loads based on aci 318-08 code. the objective function is the total cost of the frame which includes the cost of concrete, formw...

Multi-objective open-shop scheduling is definitely significant in practical. However, the research focused on multi-objective open-shop scheduling was relatively scarce. This article proposed a particle swarm optimization to address open-shop scheduling problems with multiple objectives. Originally, particle swarm optimization was invented to treat continuous optimization problems. In this pape...

This paper presents a new multi-objective optimization algorithm in which multi-swarm cooperative strategy is incorporated into particle swarm optimization algorithm, called multi-swarm cooperative multi-objective particle swarm optimizer (MC-MOPSO). This algorithm consists of multiple slave swarms and one master swarm. Each slave swarm is designed to optimize one objective function of the mult...

A new multi-objective particle swarm optimization algorithm is presented. The proposed multi-objective particle swarm optimization algorithm is based on a MaxiMin technique previously proposed for a multi-objective genetic algorithm. The technique is applied to optimize a benchmark function set and to the design of PID controllers regarding the objectives of set-point tracking and output distur...

The paper puts forward an unmanned aerial vehicle (UAV) fixed-point reconnaissance route planning method. The method introduces the improved particle swarm optimization (IPSO) method to the planning of UAV reconnaissance route and adds the objective value, effective reconnaissance route and other factors affecting UAV reconnaissance route in the objective function of particle swam to obtain the...

blind source separation technique separates mixed signals blindly without any information on the mixing system. in this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. in these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. in order to evalu...