The fruit fly optimization algorithm (FOA) is a global optimization algorithm inspired by the foraging behavior of a fruit fly swarm. In this study, a novel stochastic fractal model based fruit fly optimization algorithm is proposed for multiobjective optimization. A food source generating method based on a stochastic fractal with an adaptive parameter updating strategy is introduced to improve...

Abstract There are many complex multi-objective optimization problems in the real world, which difficult to solve using traditional methods. Multi-objective particle swarm is one of effective algorithms such problems. This paper proposes a with dynamic population size (D-MOPSO), helps compensate for lack convergence and diversity brought by optimization, makes full use existing resources search...

The structural parameters of the magnetorheological (MR) damper significantly affect output damping force and dynamic range. This paper presents a design optimization method to improve performance novel MR with bended magnetic circuit folded flow gap. multiobjective this was carried out based on optimal Latin hypercube (Opt LHD), ellipsoidal basis function neural network (EBFNN), particle swarm...

The present study proposes a low-energy consumption multipoint sampler carried by deep-sea landing vehicle (DSLV) to meet the requirements of time series sampling in local areas and location wide areas, an optimization method structure based on least-squares support-vector machine (LSSVM) surrogate model multi-objective particle swarm (MOPSO) algorithm. First, overall core components, such as s...

The time-cost trade-off problem is a known bi-objective problem in the field of project management. Recently, a new parameter, the quality of the project has been added to previously considered time and cost parameters. The main specification of the time-cost trade-off problem is discretization of the decision space to limited and accountable decision variables. In this situation the efficiency...

Vehicular Ad hoc NETworks (VANETs) are a major component recently used in the development of Intelligent Transportation Systems (ITSs). VANETs have a highly dynamic and portioned network topology due to the constant and rapid movement of vehicles. Currently, clustering algorithms are widely used as the control schemes to make VANET topology less dynamic for Medium Access Control (MAC), routing ...

Abstract Multi-objective particle swarm optimization algorithms encounter significant challenges when tackling many-objective problems. This is mainly because of the imbalance between convergence and diversity that occurs increasing selection pressure. In this paper, a novel adaptive MOPSO (ANMPSO) algorithm based on R2 contribution method developed to improve performance MOPSO. First, new glob...

With the rapid development of sensor technology and mobile services, service model crowd sensing (MCS) has emerged. In this model, user groups perceive data through carried terminal devices, thereby completing large-scale distributed tasks. Task allocation is an important link in MCS, but interests task publishers, users, platforms often conflict. Therefore, to improve performance MCS allocatio...