Maintenance scheduling of oil storage tanks using Tabu-based genetic algorithm

Sheng Tun Li, Chuan Kang Ting, Chungnan Lee, Shu Ching Chen

Research output: Contribution to journalConference articlepeer-review

4 Citations (Scopus)

Abstract

Due to the entry of Taiwan into WTO and the recently liberalized Petroleum Management Law, the oil market in Taiwan is liberalized and thus is becoming more competitive. However, the space limitation and the residents' increasing awareness of environmental protection issues in the island make international vendors unavoidably have to rent tanks from domestic oil companies. In order to help the leaseholder maximize revenue by increasing the availability of tanks, an efficient maintenance scheduling is needed. This paper introduces a tabu-based genetic algorithm (TGA) and its implementation for solving a real-world maintenance scheduling problem of oil storage tanks. TGA incorporates a tabu list to prevent inbreeding and utilizes an aspiration criterion to supply moderate selection pressure so that the selection efficiency is improved, and the population diversity is maintained. The experimental results validate that TGA outperform GA in terms of solution quality and convergence efficiency.

Original languageEnglish
Pages (from-to)209-215
Number of pages7
JournalProceedings of the International Conference on Tools with Artificial Intelligence
Publication statusPublished - 2002
Event14th International Conference on Tools with Artificial Intelligence - Washington, DC, United States
Duration: 2002 Jun 42002 Nov 6

All Science Journal Classification (ASJC) codes

  • Software

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