CAJ | 학술논문

鉴于基本粒子群算法易陷人局部最优，提出一种将混沌算法嵌入基本粒子群的混沌粒子群算法，并将其用于求解典型的资源受限项目调度问题。采用基于优先值的粒子编码方式和串行调度方案，分别用基本粒子群算法和混沌粒子群算法对实例求解。并且比较了2种算法求解多资源受限项目调度问题的性能。结果表明：混沌粒子群算法在距最优值的平均偏差和达到最优值的次数百分比等性能上要优于基本的粒子群算法，并且混沌粒子群具有更好的收敛性。但是，混沌粒子群算法在计算达到最优工期的平均时间上略比基本粒子群算法逊色。
감우기본입자군산법역함인국부최우，제출일충장혼돈산법감입기본입자군적혼돈입자군산법，병장기용우구해전형적자원수한항목조도문제。채용기우우선치적입자편마방식화천행조도방안，분별용기본입자군산법화혼돈입자군산법대실례구해。병차비교료2충산법구해다자원수한항목조도문제적성능。결과표명：혼돈입자군산법재거최우치적평균편차화체도최우치적차수백분비등성능상요우우기본적입자군산법，병차혼돈입자군구유경호적수렴성。단시，혼돈입자군산법재계산체도최우공기적평균시간상략비기본입자군산법손색。
The resource-constrained project scheduling problem is addressed in this paper. As the basic particle swarm optimization （BPSO） method is easy to be trapped in a local optimum, a chaos particle swarm optimization （CPSO） algorithm is proposed. It combines the chaos algorithm with the BPSO and is used to solve the typical multiple resources-constrained project scheduling problem. To test the perform- ance of the proposed method, both BPSO and CPSO are used to solve an instance. Comparison shows that CPSO performs better than BPSO in average deviation from the optimum and the percentage of reaching the optimal value, etc. Also, it has better convergence than BPSO. However, in the average time to achieve the optimum, the CPSO is not as good as BPSO.