A Novel Multi-Agent Evolutionary Programming Algorithm for Economic Dispatch Problems with Non-Smooth Cost Functions

This paper presents a new approach to economic dispatch (ED) problem with non-continuous and non-smooth cost functions using a hybrid evolutionary programming (EP) algorithm. In the proposed method the concept of multi-agent (MA) systems and EP are integrated together to form a new multi-agent evolutionary programming (MAEP) approach. In MAEP, an agent represents a candidate solution to the optimization problem in hand, and all agents live together in a global environment. Each agent senses its local environment, competes with its neighbors, and also learns by using its own knowledge. MAEP uses these agent-agent interactions and the evolutionary mechanism of EP to obtain the optimal solution. Numerical results show that the proposed method is more effective than other previously developed evolutionary computation algorithms in the literature.