A stochastic-fuzzy multi agent model for scheduling and portfolio selection of project by considering environmental and economic resilience

Document Type : Original Article

Authors

1 Department of Industrial Engineering, Faculty of Engineering, SR.C., Islamic Azad University, Tehran, Iran

2 Department of Industrial Engineering, Karaj Branch, Islamic Azad University, Karaj, Iran

3 Department of Industrial Engineering, Parand Branch, Islamic Azad University, Parand, Iran

Abstract
Aim of this research is to provide a stochastic fuzzy model for scheduling and selection of project portfolio in multi model sustainable and resilience condition. In real environments projects are executed in multi modes and the aim of sustainability maximization and resilience in project portfolio are pursued. For this goal librarian studies have been done based on this, a stochastic fuzzy programming model was implemented that aim to schedule and select sustainable and resilience project in multimode situation. Model was validated and was solved in small dimension. Then it was analyzed by two algorithms NSGAII and MOPSO. Results indicate that NSGAII has better performance then MOPSO and is more efficient. The most of influencing is on current value and then sustainability and resilience and sustainability is influenced by reinvestment similarly. But influencing current value from reinvestment rate is significant. Impact of loan interest on objective function is totally descending. It means if loan interest is increased all objective function can be decreased that resilience most of others and then sustainability and finally current value is decreased. It seems this function are decreased between 17 to 23 percent in 50 percent increase of loan interest.

Keywords


  1. Liu, Y.-J., & Zhang, W.-G. (2019). Flexible time horizon project portfolio optimization with consumption and risk control. Applied Soft Computing, 76, 282–293.

     Aouam, T., & Vanhoucke, M. (2019). An agency perspective for multi-mode project scheduling with time/cost trade-offs. Computers & Operations Research, 105,   167–186.

     Shafahi, A., & Haghani, A. (2018). Project selection and scheduling for phase-able projects with interdependencies among phases. Automation in Construction, 93, 47–62

    Wei, H., Niu, C., Xia, B., Dou, Y., & Hu, X. (2020). A refined selection method for project portfolio optimization considering project interactions. Expert Systems with Applications, 142, 112952. https://doi.org/10.1016/j.eswa.2019.112952

     Tavana, M., Khosrojerdi, G., Mina, H., & Rahman, A. (2019). A hybrid mathematical programming model for optimal project portfolio selection using fuzzy inference system and analytic hierarchy process. Evaluation and program planning, 77, 101703. https://doi.org/10.1016/j.evalprogplan.2019.101703

     Tavana, M., Khosrojerdi, G., Mina, H., & Rahman, A. (2020). A new dynamic two-stage mathematical programming model under uncertainty for project evaluation and selection. Computers & Industrial Engineering, 149, 106795. https://doi.org/10.1016/ j.cie.2020.106795

    Vahid Mohagheghi • Seyed Meysam Mousavi • Reza Shahabi-Shahmiri(2022), Sustainable project portfolio selection and optimization with considerations of outsourcing decisions, financing options and staff assignment under interval type-2 fuzzy uncertainty, Neural Computing and Applications (2022) 34:14577–14598 https://doi.org/10.1007/s00521-022-07207-3

    Maciej Nowak1 · Tadeusz Trzaskalik(2020), A trade‑off multiobjective dynamic programming procedure and its application to project portfolio selection, Annals of Operations Research https://doi.org/10.1007/s10479-020-03907-y

     Mojtaba Ranjbar , Mohammad Mahdi Nasiri *, S. Ali Torabi(2022),   Multi-mode project portfolio selection and scheduling in a build-operate-transfer environment, Expert Systems With Applications 189 (2022) 116134

    Kyle Robert Harrison, Saber M. Elsayed, Ivan L. Garanovich, Terence Weir, Sharon G. Boswell, and Ruhul Amin Sarker(2022), A New Model for the Project Portfolio Selection and Scheduling Problem with Defence Capability Options, Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling, Adaptation, Learning, and Optimization 26,

    https://doi.org/10.1007/978-3-030-88315-7_5

    Javier Panadero1 et al. 2022, A Variable Neighborhood Search Simheuristic for Project Portfolio Selection under Uncertainty

    Libiao Bai a, Jieyu Bai a, Min An(2022), A methodology for strategy-oriented project portfolio selection taking dynamic synergy into considerations, Alexandria Engineering Journal (2022) 61, 6357–6369

     Amin Mahmoudi a, Mehdi Abbasi b, Xiaopeng Deng(2022),   A novel project portfolio selection framework towards organizational resilience: Robust Ordinal Priority Approach, Expert Systems With Applications 188 (2022) 116067

     Libiao Bai *, Xiao Han , Hailing Wang , Kaimin Zhang , Yichen Sun(2021),   A method of network robustness under strategic goals for project portfolio selection, Computers & Industrial Engineering 161 (2021) 107658

    Ma, J., Harstvedt, J.D., Jaradat, R., Smith, B., Sustainability Driven Multi-Criteria Project Portfolio Selection under the Uncertain Decision-Making Environment, Computers & Industrial Engineering (2019), doi: https://doi.org/10.1016/j.cie.2019.106236

    Vijaya Dixit1 · Manoj Kumar Tiwari(2020), Project portfolio selection and scheduling optimization

    based on risk measure: a conditional value at risk approach, Annals of Operations Research (2020) 285:9–33 https://doi.org/10.1007/s10479-019-03214-1

    Kyle Robert Harrisona,_, Saber M. Elsayeda, Terence Weirb, Ivan L. Garanovichb, Sharon G. Boswellb, Ruhul A. Sarkera(2022), Solving a Novel Multi-divisional Project Portfolio Selection and Scheduling Problem, Preprint submitted to Engineering Applications of Arti_cial Intelligence

     Charl Maree,  Christian W. Omlin(2022),   Balancing Profit, Risk, and Sustainability for Portfolio Management, 285:9–33 https://doi.org/10.1007/s10479-019-03214-1

    1. Fu and H. Zhou. A combined multi-agent system for distributed multi-project scheduling problems. Applied Soft Computing Journal 107 (2021) 107402

    Li, F., Xu, Z., Li, H., A Multi-Agent Based Cooperative Approach to Decentralized Multi-Project Scheduling and Resource Allocation, Computers & Industrial Engineering (2020), doi: https:// doi.org/10.1016/j.cie.2020.106961

    Ayough, A., Shargh, S. B., & Khorshidvand, B. (2023). A new integrated approach based on base-criterion and utility additive methods and its application to supplier selection problem. Expert Systems with Applications, 221, 119740.

    Ayough, A., Boshruei, S., & Khorshidvand, B. (2022). A new interactive method based on multi-criteria preference degree functions for solar power plant site selection. Renewable Energy, 195, 1165-1173.

    Ayough, A., Rabieh, M., Javadi, M. N., & Khorshidvand, B. (2024). An MINLP model for project scheduling with feeding buffer. International Journal of Applied Decision Sciences, 17(6), 710-7