CAJ | 학술논문

蚁群算法是近年出现的一种新启发式算法,在求解NP完全问题中具有较大优势.针对如何在满足任务约束关系的条件下用蚁群算法求解任务分配与调度问题,首先对任务的分配与调度问题建立数学模型,然后在满足子任务之间的约束关系的条件下用蚁群算法求出最优解,最后把用蚁群算法与遗传算法的最优解进行比较.通过仿真实验表明,蚁群算法比遗传算法在任务分配与调度求解中有较高的解的质量,但蚁群算法的求解速度要慢于遗传算法.
의군산법시근년출현적일충신계발식산법,재구해NP완전문제중구유교대우세.침대여하재만족임무약속관계적조건하용의군산법구해임무분배여조도문제,수선대임무적분배여조도문제건립수학모형,연후재만족자임무지간적약속관계적조건하용의군산법구출최우해,최후파용의군산법여유전산법적최우해진행비교.통과방진실험표명,의군산법비유전산법재임무분배여조도구해중유교고적해적질량,단의군산법적구해속도요만우유전산법.
Ant colony algorithm which has a large advantage for solving NP -complete problems is a recent emergence of heu-ristic algorithms.In order to solve the problem how to use ant colony algorithm for task matching and scheduling under the con -ditions of meeting task constraints.First of all, this paper establishes the mathematical model of task matching and schedu-ling.Then the optimal solution is obtained by ant colony algorithm under the condition of task matching and scheduling .Final-ly it is compared with genetic algorithm′s solution.It is manifested by simulation experiments that the solution of ant colony al-gorithm is better than genetic algorithm but the speed of ant colony algorithm is slower than genetic algorithm .