A Compromise Programming to Task Assignment Problem in Software Development Project

The scheduling process that aims to assign tasks to members is a difficult job in project management. It plays a prerequisite role in determining the project’s quality and sometimes winning the bidding process. This study aims to propose an approach based on multi-objective combinatorial optimizatio...

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Bibliographic Details
Published in:Computers, materials & continua materials & continua, 2021, Vol.69 (3), p.3429-3444
Main Authors: Tung Son, Ngo, Jaafar, Jafreezal, Abdul Aziz, Izzatdin, Ngoc Anh, Bui, Duc Binh, Hoang, Umar Aftab, Muhammad
Format: Article
Language:English
Subjects:
Combinatorial analysis
Critical path
Decision making
Genetic algorithms
Human resources
Minimum cost
Multiple objective analysis
Operations research
Optimization
Project management
Schedules
Search process
Software development
Task scheduling
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Summary:The scheduling process that aims to assign tasks to members is a difficult job in project management. It plays a prerequisite role in determining the project’s quality and sometimes winning the bidding process. This study aims to propose an approach based on multi-objective combinatorial optimization to do this automatically. The generated schedule directs the project to be completed with the shortest critical path, at the minimum cost, while maintaining its quality. There are several real-world business constraints related to human resources, the similarity of the tasks added to the optimization model, and the literature’s traditional rules. To support the decision-maker to evaluate different decision strategies, we use compromise programming to transform multi-objective optimization (MOP) into a single-objective problem. We designed a genetic algorithm scheme to solve the transformed problem. The proposed method allows the incorporation of the model as a navigator for search agents in the optimal solution search process by transferring the objective function to the agents’ fitness function. The optimizer can effectively find compromise solutions even if the user may or may not assign a priority to particular objectives. These are achieved through a combination of non-preference and preference approaches. The experimental results show that the proposed method worked well on the tested dataset.
ISSN:1546-2226
1546-2218
1546-2226
DOI:10.32604/cmc.2021.017710