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Feasible Task Schedules With Minimum Project Cost Solved By A Genetic Algorithm

机译:用遗传算法解决项目成本最小的可行任务计划

摘要

Suppose that a project consists of n separate tasks and one and only one task can be completed in one time period. However, since some tasks can be started only before others have been completed, only feasible task schedules are considered. There is a cost associated with the time at which a task is completed and the project cost is equal to the sum of all the task costs. How can a feasible task schedule with minimum project cost be found for completing the entire project? This research proposes using a genetic algorithm to solve this problem efficiently.
机译:假设一个项目包含n个单独的任务,并且一个时间段内只能完成一项任务。但是,由于某些任务只能在其他任务完成之前启动,因此仅考虑可行的任务计划。与完成任务的时间相关的成本,项目成本等于所有任务成本的总和。如何找到一个成本最低的可行任务时间表来完成整个项目?这项研究提出使用遗传算法来有效地解决这个问题。

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