A new formulation of bi-objective optimization for the general capacitor placement and sizing problem is presented. The objectives include energy loss reduction, investment cost minimization, and maximum voltage deviation improvement. The operating and expansion constraints of the system are considered for practical needed. Also, both fixed and switched types of capacitors are included. A parti...

Traditional mathematical algorithms are incapable of solving real time engineering design problems because of its rigid procedure mainly due to discrete or random data and multi-objective functions in a problem. An optimization algorithm is a procedure which is executed iteratively by comparing various solutions till the optimum or a satisfactory solution is found. There are two population base...

Particle swarm optimization (PSO) and differential evolution (DE) are meta-heuristics which have been found to be very successful in a wide variety of optimization tasks. The high convergence rate of PSO and the exploratory capabilities of DE make them highly viable candidates to be used for solving multi-objective optimization problems (MOPs). In previous studies that we have undertaken [2], w...

this paper presents a new hybrid method for optimal multi-objective reconfiguration in a distribution feeder in addition to determining the optimal size and location of multiple-distributed generation (dg). the purposes of this research are mitigation of losses, improving the voltage profile and equalizing the feeder load balancing in distribution systems. to reduce the search space, the improv...

In this paper, a new method is proposed for solving the data clustering problem using Cat Swarm Optimization (CSO) algorithm based on chaotic behavior. The problem of data clustering is an important section in the field of the data mining, which has always been noted by researchers and experts in data mining for its numerous applications in solving real-world problems. The CSO algorithm is one ...

Many industrial sectors are concerned on developing optimal maintenance planning because of the importance of maintenance on the economy and safety. Traditionally, the maintenance planning is formulated in terms of a multi-objective optimization problem where reliability, availability, maintainability and cost act as decision criteria and surveillance test and maintenance strategies act as deci...

The main objective of this paper is to investigate the enhancement of power system stability via coordinated tuning of Power System Stabilizers (PSSs) in a multi-machine power system. The design problem of the proposed controllers is formulated as an optimization problem. Chaotic catfish particle swarm optimization (C-Catfish PSO) algorithm is used to minimize the ITAE objective function. The p...