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A multi-objective model for multi-project scheduling and multi-skilled staff assignment for IT product development considering competency evolution

Author

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  • Rong Chen
  • Changyong Liang
  • Dongxiao Gu
  • Joseph Y-T. Leung

Abstract

We address a multi-skill project scheduling problem for IT product development in this article. The goal is for product development managers to be able to generate an initial schedule at an early stage of development activities. Due to the complexity of the product structure and functionality, an IT product development effort is divided into multiple projects. Each project includes several tasks, and each task must be completed by an employee who has mastered a certain skill to complete it. A pool of multi-skilled employees is available, and the employees’ skill efficiencies are influenced by both learning and forgetting phenomena. Based on the real-world demands of product development managers, three objectives are simultaneously considered: skill efficiency gain, product development cycle time and costs. To solve this problem, we propose a multi-objective non-linear mixed integer programming model. The Non-dominated Sorting Genetic Algorithm II (NSGA-II)is designed to generate an approximation to the optimal Pareto front of this NP-hard multi-objective optimisation problem. The algorithm produces feasible schedules for all the development projects using the serial schedule generation scheme. We adopt penalty values and individual employee adjustments to address resource conflicts and constraint violations. A weighted ideal point method is used to select the final solution from the approximate Pareto solution set. An application case of a new electrical energy saving product implementation in a leading electrical device company in China is used to illustrate the proposed model and algorithm.

Suggested Citation

  • Rong Chen & Changyong Liang & Dongxiao Gu & Joseph Y-T. Leung, 2017. "A multi-objective model for multi-project scheduling and multi-skilled staff assignment for IT product development considering competency evolution," International Journal of Production Research, Taylor & Francis Journals, vol. 55(21), pages 6207-6234, November.
  • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:21:p:6207-6234
    DOI: 10.1080/00207543.2017.1326641
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    References listed on IDEAS

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    Cited by:

    1. Min Wang & Guoshan Liu & Xinyu Lin, 2022. "Dynamic Optimization of the Multi-Skilled Resource-Constrained Project Scheduling Problem with Uncertainty in Resource Availability," Mathematics, MDPI, vol. 10(17), pages 1-20, August.
    2. Minh Phuoc Doan & Julien Fondrevelle & Valérie Botta-Genoulaz & Jose Francisco Ferreira Ribeiro, 2022. "Impact of flexible work contracts and multi-skilled agents on a multi-objective workforce planning problem," Post-Print hal-03119408, HAL.
    3. Zhiping Zuo & Yanhui Li & Jing Fu & Jianlin Wu, 2019. "Human Resource Scheduling Model and Algorithm with Time Windows and Multi-Skill Constraints," Mathematics, MDPI, vol. 7(7), pages 1-18, July.
    4. Snauwaert, Jakob & Vanhoucke, Mario, 2023. "A classification and new benchmark instances for the multi-skilled resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 307(1), pages 1-19.
    5. Meya Haroune & Cheikh Dhib & Emmanuel Neron & Ameur Soukhal & Hafed Mohamed Babou & Mohamedade Farouk Nanne, 2023. "Multi-project scheduling problem under shared multi-skill resource constraints," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(1), pages 194-235, April.
    6. Wang, Xiong & Ferreira, Fernando A.F. & Chang, Ching-Ter, 2022. "Multi-objective competency-based approach to project scheduling and staff assignment: Case study of an internal audit project," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    7. Najafzad, Hamid & Davari-Ardakani, Hamed & Nemati-Lafmejani, Reza, 2019. "Multi-skill project scheduling problem under time-of-use electricity tariffs and shift differential payments," Energy, Elsevier, vol. 168(C), pages 619-636.

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