Abstract
this paper, we provide a Genetic Algorithm (GA) based approach for change management in Enterprise IT systems which minimizes change delay and improves change capacity. Change management evolves the implementation of change queues on the set of applications which are running on one or more servers. To implement these changes there are some constraints involved: atomic nature of changes; when a change is implemented then it cannot be interrupted; an application has a specific downtime, which causes timing constraint; applications that share same resources such as servers have overlapping downtime which causes conflicts among changes. In such complex system, scheduling of changes becomes a difficult optimization task. GA has the ability to optimize such constraint scheduling problems. Our GA base scheduling improves throughput and minimizes change delay of existing Capacity optimal Fluid Scheduling algorithm.
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