首页> 外文期刊>Journal of multiple-valued logic and soft computing >Minslack and Kangaroo Algorithms for Fuzzy Project Scheduling Problems
【24h】

Minslack and Kangaroo Algorithms for Fuzzy Project Scheduling Problems

机译:模糊项目调度问题的Minslack和Kangaroo算法

获取原文
获取原文并翻译 | 示例

摘要

This paper uses a resource allocation model to solve the project scheduling problem under fuzzy environment. We employ the uses of kangaroo algorithms and the fuzzy set theory to develop the Resource-Constrained Project Scheduling (RCPS) model under uncertainty. Our work proposes a mathematical model to deal with project scheduling problem under vagueness and presenting the framework of a heuristic approach to fuzzy RCPSP using a fuzzy parallel kangaroo and minslack scheduling method. We adopted the Parallel Kangaroo Algorithm Method to Fuzzy RCPSP. The objective is to minimize project planning time with resource limitations and to show how to create a plan with critical path analyses under fuzzy environment. We use trapezoidal fuzzy numbers for activity times and Activity-on-Arcs (AOA) representation in fuzzy critical path method (FCPM). Fuzzy RCPS is often a challenging issue in practice, due to its combinatorial nature and uncertainty. We present the application results of the computational the minslack and the Kangaroo algorithm and comparison of these two methods is also given.
机译:本文采用资源分配模型解决了模糊环境下的项目调度问题。我们利用袋鼠算法和模糊集理论来开发不确定性下的资源受限项目计划(RCPS)模型。我们的工作提出了一个数学模型来处理模糊性下的项目调度问题,并提出了一种使用模糊并行袋鼠和minslack调度方法的模糊RCPSP启发式方法的框架。对于模糊RCPSP,我们采用了并行袋鼠算法。目的是在资源有限的情况下最小化项目计划时间,并展示如何在模糊环境下使用关键路径分析来创建计划。我们将梯形模糊数用于活动时间,并在模糊关键路径法(FCPM)中使用弧上活动(AOA)表示。模糊RCPS由于其组合性质和不确定性,在实践中通常是一个具有挑战性的问题。我们介绍了minslack和Kangaroo算法的应用结果,并给出了这两种方法的比较。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号