Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Ant algorithms for discrete optimization
Artificial Life
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Simulated Annealing: Searching for an Optimal Temperature Schedule
SIAM Journal on Optimization
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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This paper investigates the use of ant-colony optimization, simulated annealing, and genetic algorithms for distribution network expansion planning (DNEP) including distributed generation (DG). It may be introduced as a combinatorial optimization method that determines the location and capacity of feeders and substations while minimizing the network loss and installation cost. In this paper, DGs are considered in the network expansion planning due to their importance in regulated distribution network. The implementation of each algorithm for DNE is described and the performance of algorithms is compared with each other. The proposed methods are successfully applied to planning a real distribution network.