CAJ | 학술논문

为了求解离散空间中的最优化问题，提出了一种二进制蝙蝠算法，并引入时变惯性因子来提高算法的全局收敛速度；在此基础上，为提高求解0-1背包问题时找到最优解的机率，利用贪心优化策略对无效的蝙蝠个体进行优化，从而给出了贪心二进制蝙蝠算法（GBBA）。仿真计算结果表明，GBBA算法在寻优能力和收敛性能方面比已有的GMBA算法都更优越。
위료구해리산공간중적최우화문제，제출료일충이진제편복산법，병인입시변관성인자래제고산법적전국수렴속도；재차기출상，위제고구해0-1배포문제시조도최우해적궤솔，이용탐심우화책략대무효적편복개체진행우화，종이급출료탐심이진제편복산법（GBBA）。방진계산결과표명，GBBA산법재심우능력화수렴성능방면비이유적GMBA산법도경우월。
For solving the optimization problem in discrete space, a Binary Bat Algorithm(BBA) is proposed, and time-varying inertia factor is introduced to improve the global convergence speed of the algorithm. In order to increase the probability of finding the optimal solution in solving 0-1 knapsack problem, greedy strategy is used in the algorithm, thus a Greedy Binary Bat Algorithm(GBBA)is proposed. Simulations show that the proposed algorithm is much superior to GMBA algorithm in searching capability and convergence performance.