Minimizing the Expected Makespan of a Project with Stochastic Activity Durations Under Resource Constraints

Creemers, Stefan

doi:10.2139/ssrn.2577819

Cited by 3 publications

(2 citation statements)

References 25 publications

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“…In this type of objective functions, which is also regarded as the objective function of the basic RCPSP, activities of the project are scheduled in a way that completion time of the project reaches the minimum amount. Taking into account the uncertainty about the duration of activities in the scheduling problem, Creemers (2015) presented a model, which minimized the expected completion time of the project. In addition to the objective function of minimizing Cmax, minimizing lateness, tardiness and earliness are regarded as other time-based objective functions.…”

Section: Time-based Objective Functionsmentioning

confidence: 99%

Resource-constrained project scheduling problem: review of past and recent developments

Habibi¹,

Barzinpour²,

Sadjadi³

2018

10.5267/j.jpm

105

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The project scheduling problem is both practically and theoretically of paramount importance. From the practical perspective, improvement of project scheduling as a critical part of project management process can lead to successful project completion and significantly decrease of the relevant costs. From the theoretical perspective, project scheduling is regarded as one of the interesting optimization issues, which has attracted the attention of many researchers in the area of operations research. Therefore, the project scheduling issue has been significantly evaluated over time and has been developed from various aspects. In this research, the topics related to Resource-Constrained Project Scheduling Problem (RCPSP) are reviewed, recent developments in this field are evaluated, and the results are presented for future studies. In this regard, first, the standard problem of RCPSP is expressed and related developments are presented from four aspects of resources, characteristics of activities, type of objective functions, and availability level of information. Following that, details about 216 articles conducted on RCPSP during 1980-2017 are expressed. At the end, in line with the statistics obtained from the evaluation of previous articles, suggestions are made for the future studies in order to help the development of new issues in this area.

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Section: Time-based Objective Functionsmentioning

confidence: 99%

Resource-constrained project scheduling problem: review of past and recent developments

Habibi¹,

Barzinpour²,

Sadjadi³

2018

10.5267/j.jpm

105

View full text Add to dashboard Cite

show abstract

“…The parameters, such as activity duration, human resource price, and resource availability, have been determined in advance instead of fluctuating. However, this is not realistic [21]. In order to get closer to the reality, some scholars proposed stochastic optimization or robust optimization for solving project scheduling problems in uncertain environments.…”

Section: Construction Scheduling and Resource Allocationmentioning

confidence: 99%

Robust Optimization for Integrated Construction Scheduling and Multiscale Resource Allocation

Tao

Chong

et al. 2018

Complexity

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This research investigates an integrated problem of construction scheduling and resource allocation. Inspired by complex construction practices, multi-time scale resources are considered for different length of terms, such as permanent staff and temporary workers. Differing from the common stochastic optimization problems, the resource price is supposed to be an uncertain parameter of which probability distribution is unknown, but observed data is given. Hence, the problem here is called Data-Driven Construction Scheduling and Multiscale Resource Allocation Problem (DD-CS&MRAP). Based on likelihood robust optimization, a multiobjective programming is developed where project completion time and expected resource cost are minimized simultaneously. To solve the problem efficiently, a double-layer metaheuristic comprised of Multiple Objective Particle Swarm Optimization (MOPSO) and interior point method named MOPSO-interior point algorithm is designed. The new solution presentation scheme and decoding process are developed. Finally, a construction case is used to validate the proposed method. The experimental results indicate that the MOPSO-interior point algorithm can reduce resource cost and improve the efficiency of resource utilization.

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A Novel Branch-and-Bound Algorithm for the Chance-Constrained RCPSP

Davari

Demeulemeester

2016

SSRN Journal

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The resource-constrained project scheduling problem (RCPSP) has been widely studied during the last few decades. In real-world projects, however, not all information is known in advance and uncertainty is an inevitable part of these projects. The chance-constrained resource-constrained project scheduling problem (CC-RCPSP) has been recently introduced to deal with uncertainty in the RCPSP. In this paper, we propose a branch-and-bound (B&B) algorithm and a MILP formulation that solve the CC-RCPSP. We introduce two different branching schemes and eight different priority rules for the proposed B&B algorithm. Since solving CC-RCPSP is computationally intractable, its sample average approximation counterpart is considered to be solved. The computational results suggest that the proposed branchand-bound procedure clearly outperforms both a proposed MILP formulation and a branch-and-cut algorithm from the literature.

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Minimizing the Expected Makespan of a Project with Stochastic Activity Durations Under Resource Constraints

Cited by 3 publications

References 25 publications

Resource-constrained project scheduling problem: review of past and recent developments

Resource-constrained project scheduling problem: review of past and recent developments

Robust Optimization for Integrated Construction Scheduling and Multiscale Resource Allocation

A Novel Branch-and-Bound Algorithm for the Chance-Constrained RCPSP

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