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首页> 外文会议>International Structural Engineering and Construction Conference(ISEC-03); 20050920-23; Shunan(JP) >A multiobjective evolutionary algorithm for improving robustness of project scheduling
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A multiobjective evolutionary algorithm for improving robustness of project scheduling

机译：一种提高项目进度表鲁棒性的多目标进化算法

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摘要

The problem of selecting the appropriate resources to perform the activities of a project so that to balance the project total duration and the project total cost is one of the most important aspects of construction projects planning. However, an inflexible scheduling, i.e. activities scheduled with a duration as short as possible, is not recommended, because the probability of undesirable delays is increased and the project management becomes hard. In this paper we are dealing with the project scheduling with two conflicting objectives simultaneously, namely maximize the robustness of scheduling, i.e. a weighted sum of total slack of project activities, and minimize the total duration of the project, when discrete time-cost relationships are allowed on project activities. A recently developed local search multiobjective evolutionary algorithm, called the Pareto Archived Evolution Strategy, and suggestions concerning the implementation of the algorithm in order to improve its time efficiency, is proposed for constructing the Pareto front of non-dominated solutions.
机译：选择合适的资源来执行项目活动以平衡项目总工期和项目总成本的问题是建设项目规划中最重要的方面之一。但是，不建议采用不灵活的计划，即以尽可能短的持续时间进行计划的活动，因为不希望的延误的可能性增加了，并且项目管理变得困难。在本文中，当离散时间-成本关系为时，我们同时处理具有两个冲突目标的项目进度，即最大化进度的鲁棒性，即项目活动总松弛的加权总和，并最小化项目的总工期。允许进行项目活动。提出了一种新近开发的局部搜索多目标进化算法，称为Pareto存档进化策略，并提出了有关实现该算法以提高其时间效率的建议，以构造非支配解的Pareto前沿。

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