Efficient Maintenance Scheduler for Near Optimum Utilization of Oil Tanks

Abstract

Due to the entry of Kuwait into WTO and the expected liberalization of petroleum management, the oil market is to become more competitive. However, the space limitation and public increasing awareness of environmental protection issues and stricter regulation passed by Environmental Public Authority (EPA) in Kuwait make the need for full utilization of oil tanks a prime requirement of a successful oil business. In order to help oil companies to achieve this and maximize revenues by increasing the availability of tanks, an efficient maintenance scheduling is needed. This study introduces a new hybrid evolutionary algorithm and its implantation for solving real-world problem of oil storage tanks. The algorithm incorporates the American Petroleum Institute (API) standard 650 for open inspection procedure to produce a near optimal schedule for maintenance though continuously preserving a population diversity that ensures solution quality and convergence efficiency. The computational results show that the proposed evolutionary algorithm outperforms existing scheduler in literature and produces a higher quality solution which means better revenues though more operational tanks and more environmental protection though maximizing the utilization of existing tanks and less new tanks to build.