Improved Dual - objective Particle Swarm Algorithm Solves the Problems of Raw Coal

نویسندگان

  • Bin WU
  • Langcai CAO
  • Jian LUO
چکیده

The blending process of raw coal‘s being sold to power plants is a optimization process of pursuing the cost minimization under certain constraints. Among all intelligent algorithms solving those kinds of optimization problems, Particle swarm optimization (PSO) algorithm is relatively a better choice. This paper describes the improvement of the PSO by turning single-objective optimization problems with constrained conditions into a dual-objective optimization problem, of which one is problem original objective function and the other is constraints. Simulation results indicate that the improved dual-objective PSO algorithm is simple and feasible, and has a good global search capability to be able to search for the optimal solution quickly. Copyright © 2013 IFSA.

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تاریخ انتشار 2013