Swarm robots are special multi-robots and usually considered being controlled with swarm intelligence-basedmethod to complete some assigned complex tasks (Dorigo and Sahin, 2004). Similar to the biological counterparts in nature, swarm intelligence among such artificial system is emerged from local interactions between individual robots or individual robot and its environment (Beni, 2005; Şahin...

A generic constraint handling framework for use with any swarm-based optimization algorithm is presented. For swarm optimizers to solve constrained optimization problems effectively modifications have to be made to the optimizers to handle the constraints, however, these constraint handling frameworks are often not universally applicable to all swarm algorithms. A constraint handling framework ...

A multiuser detector for direct-sequence code-division multiple-access systems based on particle swarm optimization (PSO) algorithm is proposed. To work around potentially computational intractability, the proposed scheme exploits heuristics in consideration of both global and local exploration maximum likelihood (ML). Computer simulation demonstrates that the proposed detector offers near-opti...

this study is investigated the optimum parameters for a tuned mass damper (tmd) under the seismic excitation. shuffled complex evolution (sce) is a meta-heuristic optimization method which is used to find the optimum damping and tuning frequency ratio for a tmd. the efficiency of the tmd is evaluated by decreasing the structural displacement dynamic magnification factor (ddmf) and acceleration ...

Sub-dimension particle swarm optimization(s-dPSO) is proposed based on basic particle swarm optimization (bPSO). Each dimension of particle in s-dPSO is updated in turn. The dimensions with poor diversity would be mutated that is initialized again to improve the diversity of population and get global optimal solution when the algorithm is in the local convergence. Most Benchmark function get go...

Landslide susceptibility analysis is beneficial information for a wide range of applications, including land use management plans. The present attempt has shed light on an efficient landslide mapping framework that involves adaptive neural-fuzzy inference system (ANFIS), which incorporates three metaheuristic methods grey wolf optimization (GWO), particle swarm (PSO), and shuffled frog leaping ...

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...

A grand challenge in the field of artificial life is to find a general theory of emergent self-organizing systems. In this paper we try to explain the emergent behavior of a simulated swarm by applying methods based on the fluctuation theorem. Empirical results indicate that the swarm is able to produce negative entropy within an isolated sub-system due to ‘frozen accidents’. Individuals of the...

In this study, a new variant of Particle Swarm Optimization, Electoral Cooperative PSO (ECPSO), is presented and applied into solving the Permutation Flow Shop Scheduling Problem (PFSSP). Firstly, an electoral swarm is generated by the voting of primitive sub-swarms and also participates in evolution of swarm, whose particle candidates come from primitive sub-swarms with variable votes from the...