A multistage stochastic programming approach in project selection and scheduling

Rafiee, Majid; Kianfar, Farhad; Farhadkhani, Mehdi

doi:10.1007/s00170-013-5362-6

Cited by 23 publications

(7 citation statements)

References 61 publications

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“…Thanks to the correlation and dynamics characterized by the time of each stage, multi-stage stochastic mathematical programming (Grossmann et al. , 2017; Rafiee et al. , 2013) is used to solve the problem of optimal payment of the government in each stage.…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, the multi-stage payment problem composed of multiple assessment periods is regarded as a multi-stage stochastic programming problem. Thanks to the correlation and dynamics characterized by the time of each stage, multi-stage stochastic mathematical programming (Grossmann et al, 2017;Rafiee et al, 2013) is used to solve the problem of optimal payment of the government in each stage. And the sketch diagram of payment amounts from the public sector at each stage for WETPPPs is shown in Figure 1.…”

Section: Description Of Research Problemmentioning

confidence: 99%

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Water environment treatment PPP projects optimal payment mechanism based on multi-stage dynamic programming model

Cao

et al. 2022

ECAM

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PurposeThe optimal payment in the whole operation and maintenance period of water environment treatment PPP projects has become the main approach to realize sustainable development of projects. This study is aimed at constructing an effective payment model for the whole life period of projects to achieve win-win among all stakeholders, so as to provide a theoretical reference and managerial implications for the public sector in the whole operation and maintenance period.Design/methodology/approachIn the whole operation and maintenance period of water environment treatment PPP projects, this article investigates how the public sector optimizes the payment in the whole operation and maintenance period of projects. Firstly, the projects' whole operation and maintenance period is divided into several stages according to the performance appraisal period. And then, the multi-stage dynamic programming model is constructed to design the payment construct model for the public sector in each performance appraisal stage. The payment from the public sector is the decision variable, and the deduction from the private sector is a random variable.FindingsThe optimal payment model showed that the relatively less objective weight of public sector leaded to its relatively more total payment and vice versa. Therefore, the sustainable development of the projects can only be ensured when the objective weights both of them should be balanced. Additionally, the deduction from the performance appraisal of private sector plays an important role in the model construction. The larger deduction the private sector undertakes, the smaller profits private sector has. Since the deduction at each stage is a random variable, the deduction varies with the different probability distributions obeyed by the practical deduction in each stage.Research limitations/implicationsThe findings from this study have provided theoretical and application references, and some managerial implications are also given. First, the improvement of the pricing system of public sector should be accelerated. Second, the reasonable profit of the private sector must be guaranteed. While pursuing the maximization of social benefits, the public sector should make full use of the price sharing mechanism in the market and supervise the real income situation of the private sector. Third is increasing the public to participate in pricing. Additionally, it is a limitation that the deduction is assumed to conform to a uniform distribution in this study. Other probability distributions on deduction can be essentially further sought, so as to be more line with the actual situation of the projects.Originality/valueThe optimal payment in whole operation and maintenance period of the projects has become an important issue, which is a key to project success. This study constructs a multi-stage dynamic programming model to optimize payment in the whole period of projects. Additionally, this study adds its value through deeply developing the new theories of optimal payment to more suitable for the practical problems, so that to optimize the design of payment mechanism. Meanwhile, a valuable reference for public and private sectors is provided to ensure the sustainable development of the projects.

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Section: Methodsmentioning

confidence: 99%

Section: Description Of Research Problemmentioning

confidence: 99%

Water environment treatment PPP projects optimal payment mechanism based on multi-stage dynamic programming model

Cao

et al. 2022

ECAM

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“…For example, Choi et al (2004) used a discretetime Markov chain and dynamic programming to address the uncertainties of durations/costs of tasks, as well as uncertainties in success/ failure of projects in an RCPSP setting. Rafiee et al (2014) proposed a multi-stage stochastic optimization model for multi-period project selection and scheduling problem. Also, Pourahmadi et al (2015) proposed a scenario-based mathematical model for project portfolio selection with stochastic parameters.…”

Section: Goalmentioning

confidence: 99%

A Sustainable Resource-Constrained Project Selection and Scheduling Model using Scenario-Based Stochastic Programming: A case study of industrial projects

Rahimi

Davari-Ardakani

Ameli

et al. 2023

Preprint

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Due to a wide variety of real-world constraints, proper project portfolio selection is a critical issue for project-oriented organizations. In this paper, a bi-objective stochastic mixed-integer linear program is developed to cope with the resource-constrained project selection and scheduling problem in the presence of greenhouse gas emissions, and non-hazardous and hazardous wastes regulatory restrictions. Moreover, reinvesting proceeds of projects as well as loans are allowed to finance projects over the planning horizon. The proposed model maximizes the net present value of the expected project portfolio's terminal wealth under uncertain conditions, as well as the sustainability score of the project portfolio, simultaneously. The sustainability score is calculated by one of the recent multi-criteria decision-making methods, SECA, based on seven qualitative sustainability indicators and by solving a non-linear optimization model. To assess the performance of the proposed model, a case study of eighteen industrial projects is applied. Since the duration of industrial projects is usually uncertain, the proposed model is reformulated as a scenario-based stochastic programming model. Furthermore, the CPLEX solver and Branch and Benders algorithm are used to solve the problem. Results show that the Branch and Benders algorithm is much more efficient than the Cplex solver. In the end, according to the performed sensitivity analysis, in some cases, increasing the carbon and landfill tax rates, does not significantly reduce the negative environmental effects, while making the projects less attractive for investment. This highlights the importance of coping with the problem under consideration for managers, legislators, and policymakers.

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“…However, if the DMsApostrophe; preference information is completely unknown, these methods are not applicable. Publications based on random theory (Rafiee, Kianfar, & Farhadkhani, ) are relatively few, and they also cannot solve the problems with unknown weights.…”

Section: Related Literaturementioning

confidence: 99%

An stochastic multiattribute acceptability analysis‐based method for the multiattribute project portfolio selection problem with rank‐level information

et al. 2019

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In many cases of practical multiattribute project portfolio selection problems, it is hard to obtain accurate measurements of attributes and precise preference information. Even after a long and costly information gathering, the attribute measurements and the preference information can still be uncertain or inaccurate. Considerable cost saving will be obtained if the selection of an optimal project portfolio can be done using rank‐level information based on some or all the attributes, without knowing the preference information. In this paper, we propose a stochastic multiattribute acceptability analysis‐based method that can deal with mixed rank and cardinal attribute measurements and uses little or no weight information. In the proposed stochastic multiattribute acceptability analysis‐based method, the decision makers need not to express their preferences explicitly or implicitly, so it is particularly useful when no weight information is available at all. A numerical example involving selection of photovoltaic plants in an industrial province in Eastern China is provided to demonstrate the proposed method.

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A multistage stochastic programming approach in project selection and scheduling

Cited by 23 publications

References 61 publications

Water environment treatment PPP projects optimal payment mechanism based on multi-stage dynamic programming model

Water environment treatment PPP projects optimal payment mechanism based on multi-stage dynamic programming model

A Sustainable Resource-Constrained Project Selection and Scheduling Model using Scenario-Based Stochastic Programming: A case study of industrial projects

An stochastic multiattribute acceptability analysis‐based method for the multiattribute project portfolio selection problem with rank‐level information

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