A Branch and Bound-PSO Hybrid Algorithm for Solving Integer Separable Concave Programming Problems

نویسندگان

  • Yuelin Gao
  • Zihui Ren
  • Chengxian Xu
چکیده

A branch and bound-PSO hybrid algorithm for solving integer separable concave programming problems is proposed, in which the lower bound of the optimal value was determined by solving linear programming relax and the upper bound of the optimal value and the best feasible solution at present were found and renewed with particle swarm optimization (PSO). It is shown by the numerical results that the branch and bound-PSO hybrid algorithm is better than the branch and bound algorithm in the computational scale and the computational time and the computational precision and overcome the convergent difficulty of particle swarm optimization (PSO).

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تاریخ انتشار 2007