CAJ | 학술논문

在工程项目管理的资源优化中应用微粒群算法，定义了微粒坐标是活动的实际开始时间的微粒群；建立了一个直接反映资源强度与活动实际开始时间之间关系的评价函数；以微粒群算法为基础，编码设计搜索最佳方案的活动实际开始时间。最后计算分析典型算例，初始方案结果比微粒群算法得到的结果高出3倍多，遗传算法的结果比微粒群算法的结果高出53．52％，由此证明了微粒群算法在工程项目管理的资源均衡优化中的可行性及有效性。
재공정항목관리적자원우화중응용미립군산법，정의료미립좌표시활동적실제개시시간적미립군；건립료일개직접반영자원강도여활동실제개시시간지간관계적평개함수；이미립군산법위기출，편마설계수색최가방안적활동실제개시시간。최후계산분석전형산례，초시방안결과비미립군산법득도적결과고출3배다，유전산법적결과비미립군산법적결과고출53．52％，유차증명료미립군산법재공정항목관리적자원균형우화중적가행성급유효성。
In this paper , when dealing with the unlimited resource leveling optimization of engineering , the PSO was applied .The particle swarm optimization whose coordinates were the actual start time of the activity was defined .Established anevaluation function who was able to reflect the relationship between the resource intensity and the actual start time of the activity directly .Based on the particle swarm optimization , searched the activity's actual start time of the best program by code design .Finally, the resource intensity obtained by initial program was more than three times higher than the particle swarm , the result of the genetic algorithm was 53 .52% higher than the swarm algorithm according to the case analysis .Thusproving the feasibility and effectiveness of PSO in the unlimited resource leveling optimization .