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A Multiagent Evolutionary Algorithm for the Resource-Constrained Project Portfolio Selection and Scheduling Problem

Author

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  • Yongyi Shou
  • Wenwen Xiang
  • Ying Li
  • Weijian Yao

Abstract

A multiagent evolutionary algorithm is proposed to solve the resource-constrained project portfolio selection and scheduling problem. The proposed algorithm has a dual level structure. In the upper level a set of agents make decisions to select appropriate project portfolios. Each agent selects its project portfolio independently. The neighborhood competition operator and self-learning operator are designed to improve the agent’s energy, that is, the portfolio profit. In the lower level the selected projects are scheduled simultaneously and completion times are computed to estimate the expected portfolio profit. A priority rule-based heuristic is used by each agent to solve the multiproject scheduling problem. A set of instances were generated systematically from the widely used Patterson set. Computational experiments confirmed that the proposed evolutionary algorithm is effective for the resource-constrained project portfolio selection and scheduling problem.

Suggested Citation

  • Yongyi Shou & Wenwen Xiang & Ying Li & Weijian Yao, 2014. "A Multiagent Evolutionary Algorithm for the Resource-Constrained Project Portfolio Selection and Scheduling Problem," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-9, April.
    • Handle: RePEc:hin:jnlmpe:302684
    DOI: 10.1155/2014/302684
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    Cited by:

    1. Gómez Sánchez, Mariam & Lalla-Ruiz, Eduardo & Fernández Gil, Alejandro & Castro, Carlos & Voß, Stefan, 2023. "Resource-constrained multi-project scheduling problem: A survey," European Journal of Operational Research, Elsevier, vol. 309(3), pages 958-976.
    2. Ran Etgar & Yuval Cohen, 2022. "Roadmap Optimization: Multi-Annual Project Portfolio Selection Method," Mathematics, MDPI, vol. 10(9), pages 1-23, May.

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