Decision-making support system for human resource allocation in product development projects

DOI10.1080/00207540500272519zbMath1095.90575OpenAlexW2016684170MaRDI QIDQ5478834

Kazuhiro Izui, Y. Fujimi, Shinji Nishiwaki, M. Yoshimura

Publication date: 13 July 2006

Published in: International Journal of Production Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207540500272519

zbMATH Keywords

Project managementSystem engineeringDecision-making support systemHuman resource allocationProduction management

Mathematics Subject Classification ID

Management decision making, including multiple objectives (90B50)

Related Items (12)

Work assignment to and qualification of multi-skilled human resources under knowledge depreciation and company skill level targets ⋮ An efficient metaheuristic for integrated scheduling and staffing IT projects based on a generalized minimum cost flow network ⋮ Scheduling and staffing multiple projects with a multi-skilled workforce ⋮ Minimizing average project team size given multi-skilled workers with heterogeneous skill levels ⋮ A MULTICRITERIA DECISION SUPPORT SYSTEM FOR COMPETENCE-DRIVEN PROJECT PORTFOLIO SELECTION ⋮ Optimal dynamic portfolio selection for projects under a competence development model ⋮ Resource constrained routing and scheduling: review and research prospects ⋮ An improved MIP-based approach for a multi-skill workforce scheduling problem ⋮ Bi-objective project portfolio selection and staff assignment under uncertainty ⋮ Skill-based framework for optimal software project selection and resource allocation ⋮ Multi-objective decision analysis for competence-oriented project portfolio selection ⋮ Multi-objective human resources allocation in R&D projects planning

Cites Work

• Multi-period job selection: Planning work loads to maximize profit
• Resource-constrained project scheduling: A survey of recent developments.
• Order acceptance strategies in a production-to-order environment with setup times and due-dates
• Heuristic approach for assigning workers to tasks based on individual learning rates

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