4.4 Article

A Hybrid Algorithm for Solving Resource-Constrained Project Scheduling Problems with Fuzzy Activity Durations: An Application in Disc Mower Manufacturing Project

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OLD CITY PUBLISHING INC

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Resource-constrained project scheduling; disc mower manufacturing project; fuzzy numbers; hybrid parallel kangaroo algorithm; project delay risk; minimum satisfaction values

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Determining resource requirements and activity durations accurately is crucial in project scheduling. This study proposes a hybrid algorithm to generate realistic project schedules with minimal risk of delay. The algorithm is tested on benchmark problems and a real-world case, showing promising results.
Determining the resource requirements and the duration of activities are crucial points in project scheduling. Completing a project on planned time heavily depends on the activity durations and resources, which should be determined as accurately and precisely as possible. A Hybrid parallel kangaroo algorithm (HPKA) is developed to cope with this problem and prepare more realistic project schedules that could be executed in time with the minimum risk of being late. The objective is to find a schedule that minimizes schedule risk and maximizes the minimum satisfaction degrees of all activities. The proposed hybrid algorithm is tested with the benchmark problems from the literature. The proposed HPKA is then used to solve a disc mower manufacturing project scheduling problem of a real-world company that manufactures agricultural machinery. The results indicate that the proposed hybrid algorithm can achieve good results for these problems.

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