The problem of the distribution of dairy products, which is classified as a combinatorial optimization problem, cannot be solved in polynomial time. In this paper, an algorithm based on Ant Colony Hybrid meta-heuristic system and Geographic Information System (GIS) was used to find a near-optimal solution to this problem. Using the former method, the nearest neighbor heuristic algorithm was use...

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...

the operation of a distribution system in the presence of distributed generation systems has someadvantages and challenges. optimal sizing and siting of dg systems has economic, technical, andenvironmental benefits in distribution systems. improper selection of dg systems can reduce theseadvantages or even result in deterioration in the normal operation of the distribution system. dgallocation ...

Charged particle swarm optimization (CPSO) is well suited to the dynamic search problem since inter-particle repulsion maintains population diversity and good tracking can be achieved with a simple algorithm. This work extends the application of CPSO to the dynamic problem by considering a bi-modal parabolic environment of high spatial and temporal severity. Two types of charged swarms and an a...

This paper proposes a novel hybrid algorithm namely APSO-BFO which combines merits of Bacterial Foraging Optimization (BFO) algorithm and Adaptive Particle Swarm Optimization (APSO) algorithm to determine the optimal PID parameters for control of nonlinear systems. To balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...

This paper proposes a novel hybrid algorithm namely APSO-BFO which combines merits of Bacterial Foraging Optimization (BFO) algorithm and Adaptive Particle Swarm Optimization (APSO) algorithm to determine the optimal PID parameters for control of nonlinear systems. To balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...

gravitational search algorithm (gsa) is one of the newest swarm based optimization algorithms, which has been inspired by the newtonian laws of gravity and motion. gsa has empirically shown to be an efficient and robust stochastic search algorithm. since introducing gsa a convergence analysis of this algorithm has not yet been developed. this paper introduces the first attempt to a formal conve...