An Entropy and Artificial Bee Colony Approach for the Multi-Mode Resource Constrained Project Scheduling Problem  

Oleh:

Chen, Angela Hsiang-Ling ; Liang, Yun-Chia ; Padilla, J David

Jenis: Article from Proceeding
Dalam koleksi: The 14th Asia Pacific Industrial Engineering and Management Systems Conference (APIEMS), 3-6 December 2013 Cebu, Philippines, page 1-8.
Topik: Production & Operations Management; Scheduling & Sequencing; Meta-heuristics; Optimization/Artificial Intelligence Techniques
Fulltext: 1269.pdf (357.94KB)

Isi artikel

Whichever the purpose for which a project is developed, and regardless of if it is executed by common citizens or world-wide corporations, every project has at least two things in common: limited resources and uncertainty. In practice, every project usually has more than one way in which it can be completed and generally a schedule is required in such a way that it makes the best possible use of the limited resources to complete the project in the shortest possible time. In the academic world, this is known as the Multi-mode Resource Constrained Project Scheduling Problem, a widely researched, NP-complete problem. However, not much research has been made on how to make the schedules not only short, and with efficient use of the resources but also flexible enough to withstand the variations caused by the uncertain environment. This study therefore focuses on how to use an entropy function that generates buffer times only dependent on the activities duration and their relationships, starting from a previously optimized schedule. The optimal schedule is found with the help of a proven effective and powerful recent meta-heuristic algorithm, artificial bee colony (ABC). The computational results indicate that it is possible to generate schedules with enough buffer time to absorb small variations, and generally result in an increase of less than 10% of the optimized makespan.

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