## 1 Introduction  
In general, power systems are designed to work with unidirectional power flow due to the lack of power source, except for the main generating power plants [1]. In the meanwhile, the introduction of distributed generation (DG) has changed the fundamental way of the operation in the power system distribution network from passive to active network [2]. Distributed generation can effectively functioning in the distribution system in order to give additional support to the main grid by satisfying load demand, enhancing voltage profile, improving reliability and reducing power losses [3]. The reduction of power losses is very important to maintain the efficiency of the distribution system. There are several approaches to overcome the power losses problems such as network reconfiguration as well as capacitor and DG installation. However, the benefits of these approaches can be achieved if they are carefully coordinated in the distribution system [4]. By examining the literature, it seems that only a few approaches have been proposed to take care of this issue. Research in [5; 6; 7], for example, have used DG approach only for mitigating voltage stability problem without considering other alternatives such as network reconfiguration. In general meta-heuristic based optimization techniques are the most prominent method for solving the coordination problems due to its robustness and simplicity [8]. There are many examples of these methods for such an optimization problem. These methods include simulated annealing (SA), particle swarm optimization (PSO), firefly algorithm (FA), artificial immune system (AIS), harmony search algorithm (HAS) and artificial bee colony (ABC). Furthermore, hybridized optimization methods are also proposed by combining two optimization techniques [8]. Among these optimization methods, PSO has become very popular, due to its simplicity and its affinity towards manufacturing and robotics, electrical power systems, engineering and other areas [9]. Therefore, this paper focuses on swarm optimization as a selected algorithm to solve the problem regarding power losses and voltage stability. In classical PSO cases, PSO sometimes fail to find a global optimum solution. The problem occurs due to the fact that the particles are trapped at a local optimum solution [9]. Therefore, this paper proposes a new optimization algorithm known as improved evolutionary particle swarm optimization (IEPSO) to handle simultaneous approach (distribution network reconfiguration (DNR) and DG) for power loss reduction and to alleviate the problem of voltage stability as well. This paper is organized as follows, introduction and a section that shows the optimization process of the active distribution networks concept including objective functions and constrains (Section 2). After that, a section that explains the proposed optimization problem is provided. Following that the optimization process is discussed in a separated section (Section 4) and then a detailed results section is provided (Section 5) followed by a conclusion section. Optimization of Active Distribution Networks for Voltage Stability Improvement and Power Loss Reduction  
The decline of voltage stability is one of the important factors which restrict the increase of load served by distribution networks [10]. Therefore, it is necessary to analyze voltage stability with the variation of load levels in distribution networks that includes DG unit. In [8] the authors have suggested that voltage stability should be taken as an objective function when addressing the optimal placement of DG units. In addition, two notable studies [6; 11] formulated approaches that can be utilised to identify effective placements for DG units to heighten the voltage profile and voltage stability of distribution network. Voltage instability in distribution systems has been understood for decades and was referred to as load instability [12].