The Global Software Engineering (GSE) team works across geography. Project planning is one important phase before starting with the actual work, for any type of project. Planning involves discussion with multiple stakeholder before the plan to put up in the plan sheet. In today’s working environment with respect to the industry most of the time the planning will go through the change due to several factors like talent availability, technical competencies, requirement understanding, etc. it is very important to maintain the project plan as it directly links with the project success. Currently the plan is majorly maintained by excel or some planning tool available in the market. Still there is much manual effort involved to maintain the plan. The impact is due to any reason of delay, the plan affects, the changes are not covered completely. In this work trying to apply the Plan Assess React (PAR) approach that reviewing the plan periodically with proper findings and solutioning effectively. So, in this work the intend to address the optimization of the tactical planning for the fast-growing software industry using the Plan Assess React (PAR) approach using Genetic Algorithm with an AI inclusive. This is going to help in validating the plan with each check activity progress, on any change occurs update and maintain successfully. To bring the optimization as the work focus on, the approach used here is the Genetic algorithm as it is a proven study and very helpful to give the near real time optimal solution. Also, the AI is used here in the methodology to apply technology advancement for the automation and reduce the manual work as well. Based on the study the merge of Genetic algorithm with an AI is a good fit-in for the result of optimization. Hence this work showcases the proactive planning using the Genetic algorithm approach with an AI inclusive and foreseeing the active phase of any project for a program. With this work will directly benefit the industry people, project managers, and the researchers.

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Optimizing Software Engineering Project Plan Using Genetic Algorithm and AI

  • K. M. Harini Kannamma,
  • G. S. R. Emil Selvan,
  • M. P. Ramkumar,
  • Sridaran Rajagopal

摘要

The Global Software Engineering (GSE) team works across geography. Project planning is one important phase before starting with the actual work, for any type of project. Planning involves discussion with multiple stakeholder before the plan to put up in the plan sheet. In today’s working environment with respect to the industry most of the time the planning will go through the change due to several factors like talent availability, technical competencies, requirement understanding, etc. it is very important to maintain the project plan as it directly links with the project success. Currently the plan is majorly maintained by excel or some planning tool available in the market. Still there is much manual effort involved to maintain the plan. The impact is due to any reason of delay, the plan affects, the changes are not covered completely. In this work trying to apply the Plan Assess React (PAR) approach that reviewing the plan periodically with proper findings and solutioning effectively. So, in this work the intend to address the optimization of the tactical planning for the fast-growing software industry using the Plan Assess React (PAR) approach using Genetic Algorithm with an AI inclusive. This is going to help in validating the plan with each check activity progress, on any change occurs update and maintain successfully. To bring the optimization as the work focus on, the approach used here is the Genetic algorithm as it is a proven study and very helpful to give the near real time optimal solution. Also, the AI is used here in the methodology to apply technology advancement for the automation and reduce the manual work as well. Based on the study the merge of Genetic algorithm with an AI is a good fit-in for the result of optimization. Hence this work showcases the proactive planning using the Genetic algorithm approach with an AI inclusive and foreseeing the active phase of any project for a program. With this work will directly benefit the industry people, project managers, and the researchers.