This paper puts forward a new automatic clustering algorithm based on Multi-Objective Particle Swarm Optimization and Simulated Annealing, "MOPSOSA". The proposed algorithm is capable of automatic clustering which is appropriate for partitioning datasets to a suitable number of clusters. MOPSOSA combines the features of the multi-objective based particle swarm optimization (PSO) and the Multi-O...

In the quest to achieve home comfort with highest possible efficiency, there is an increasing interest in combined cooling, heating and power (CCHP) systems. These can be fuelled by natural gas potentially hydrogen enriched ultimately hydrogen. The optimised designs largely depend on energy dispatch algorithms that take into account aspects of economic environmental impacts as well system effic...

Oscillations are an intrinsic phenomenon in interconnected power systems, leading to steady-state stability, safety decline, transmission limitation, and electric systems’ ineffective exploitation by developing particularly connecting these systems low-load lines. In addition, they affect the economic performance of systems. this study, PSS2B system stabilizers TCSC compensators used improve st...

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...

Big data is a commodity that highly valued in the entire globe. It not just regarded as but world of experts, we can derive intelligence from it. Because its characteristics which are Variety, Value, Volume, Velocity, and growing need how it be handled, Organizations facing difficulties ensuring optimal well affordable processing storage large datasets. One already existing models used for rapi...

This paper presents a novel scheduling of resource-constrained Flexible Manufacturing System (FMS) with consideration the following sub-problems: (i) machine loading and unloading, (ii) manufacturing operation scheduling, (iii) assignment, (iv) Automated Guided Vehicle (AGV) scheduling. In proposed model, both AGV machinery are considered as required resources. Energy efficiency AGVs has been s...

Shared manufacturing is recognized as a new point-to-point mode in the digital era. referred to realize dynamic allocation of tasks and resources. Compared with traditional mode, shared offers more abundant resources flexible configuration options. This paper proposes model based on description environment, characteristics resource allocation. The execution tasks, which candidate enter or exit ...

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...

In this paper, we proposed an algorithm for solving the problem of task scheduling using particle swarm optimization algorithm, with changes in the Selection and removing the guide and also using the technique to get away from the bad, to move away from local extreme and diversity. Scheduling algorithms play an important role in grid computing, parallel tasks Scheduling and sending them to ...