A genetic algorithm for scheduling multimode resource-constrained project problem in the presence of preemptive resources

Delgoshaei, Aidin; Hanjani, Sepehr Esmaeili; Nasiri, Amir Hossein

doi:10.5267/j.jpm.2019.3.005

Cited by 6 publications

(6 citation statements)

References 33 publications

(35 reference statements)

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“…They proposed a new genetic algorithm using a two-point crossover operator. Delgoshaei et al (2019) developed a multi-objective nonlinear mixed integer programming model where resource availability was not deterministic and expressed by triangular probability function. In addition, a multi-objective weighting genetic algorithm was proposed.…”

Section: Literature Reviewmentioning

confidence: 99%

Blockchain of Optimal Multiple Construction Projects Planning Under Probabilistic Arrival and Stochastic Durations

Al–Refaie

Al-Hawadi

Lepkova

et al. 2023

Journal of Civil Engineering and Management

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With the rapid development of projects, firms are facing challenges in planning and controlling complex multiple construction projects. This research, therefore, aims at developing blockchain of optimal scheduling and sequencing of multiple construction projects under probabilistic arrival and stochastic durations. Each project task was considered as a block. Then, a framework for electronic project recording (EPR) system was developed. The EPRs are records for project tasks that make information available directly and securely to authorized users. In this framework, two optimization models were developed for scheduling and sequencing project blocks. The scheduling model aims to assign project tasks to available resources at minimal total cost and maximal the number of assigned project tasks. On the other hand, the sequencing model seeks to determine the start time of block execution while minimizing delay costs and minimizing the sum of task’s start times. The project arrival date and the task’s execution duration were assumed probabilistic and stochastic (normally distributed), respectively. The developed EPR system was implemented on a real case study of five projects with total of 121 tasks. Further, the system was developed when the task’s execution duration follows the Program Evaluation and Review Technique (PERT) model with four replications. The project costs (idle time and overtime costs) at optimal plan were then compared between the task’s execution duration normally distributed and PERT modelled. The results revealed negligible differences between project costs and slight changes in the sequence of project activities. Consequently, both distributions can be used interchangeably to model the task’s execution duration. Furthermore, the project costs were also compared between four solution replications and were found very close, which indicates the robustness of model solutions to random generation of task’s execution duration at both models. In conclusion, the developed EPR framework including the optimization models provided an effective planning and monitoring of construction projects that can be used to make decisions through project progress and efficient sharing of project resources at minimal idle and overtime costs. Future research considers developing a Blockchain of optimal maintenance planning.

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Section: Literature Reviewmentioning

confidence: 99%

Blockchain of Optimal Multiple Construction Projects Planning Under Probabilistic Arrival and Stochastic Durations

Al–Refaie

Al-Hawadi

Lepkova

et al. 2023

Journal of Civil Engineering and Management

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“…T S and C S are the dimensionless index values of the total project construction period and total cost of individual projects, respectively. For dimensionless treatment, see formulas (11) and (12).…”

Section: Fitness Functionmentioning

confidence: 99%

“…Literature [10] transformed RIP into an RCPSP problem, which was solved by the metaheuristic algorithm based on Scatter Search. Literature [11] uses a genetic algorithm to solve the resource input problem with delay penalty and codes the job priority and resource capacity respectively. Literature [12] solved the RIP problem by path reconnection and genetic algorithm for the first time without transforming the RIP problem into RCPSP.…”

Section: Introductionmentioning

confidence: 99%

A Genetic Algorithm Model for Human Resource Management Optimization in the Internet Marketing Era

Linna

2022

Mathematical Problems in Engineering

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In the context of the Internet marketing era, rational use of big data for quantitative analysis of human resource management can effectively help each unit better understand the industry talent and analyze the development trend of the industry. Personnel competency is the key factor affecting job performance. The renewable resources in the resource constrained project scheduling problem are transformed into human resources with competency differences through a series of scientific and reasonable methods. A human resource constrained project scheduling problem model emphasizing competency differences is constructed. The most prominent advantage of this model lies in the selection of indicators that can objectively and reasonably evaluate the competency of personnel, and the rigorous and scientific relationship is provided. The complex multiproject double-objective minimization problem of the total construction period and total cost is transformed into a comprehensive index single-objective maximization problem. Then, a mathematical optimization model is established and solved by a genetic algorithm. Finally, the effectiveness of the algorithm is shown by comparing numerical experiments with other algorithms.

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“…e PRCPSP (Preemptive Resource-Constrained Project Scheduling Problem) mathematical model aiming at the shortest maintenance time and the minimum total load of maintenance personnel is established in references [6][7][8]. Literature [9] introduces GPRs (Generalized priority relation) and AON (Activity-On-Node) to describe the sequential relationship of tasks and uses an improved cuckoo algorithm to solve the problem.…”

Section: Introductionmentioning

confidence: 99%

Maintenance Personnel Optimization Model of Vehicle Equipment Based on Support Task

Song

Lei²,

Qian³

et al. 2021

Mathematical Problems in Engineering

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Vehicle equipment maintenance support tasks have problems such as low maintenance efficiency and unreasonable allocation of maintenance personnel. In order to further strengthen the theoretical research of vehicle equipment maintenance support, an optimization model of vehicle equipment maintenance personnel based on support task is proposed in this paper. Firstly, the maintenance workload model of vehicle equipment is constructed by analyzing the three task sources of vehicle equipment: scheduled maintenance, natural random failure, and combat damage. Then, considering the technical professional level, maintenance efficiency, and other factors of maintenance personnel, two optimization models of maintenance personnel are constructed. In view of the situation where there are enough human resources, the prediction model of the number of personnel with the minimum total number as the goal is constructed to achieve the purpose of saving human resources. Using MATLAB mixed integer nonlinear programming problem (MINP) toolbox to solve the prediction model of the number of personnel, in view of the shortage of maintenance personnel, a maintenance personnel allocation model aiming at minimizing maintenance time is constructed to maximize maintenance efficiency. In order to solve the model, the fruit fly optimization algorithm (FOA) is improved, and the group cooperation is used to update the fruit fly position. The new algorithm not only retains the essential advantages of the FOA but also solves the problem that the algorithm is easy to fall into local extreme value and improves the global optimization ability of the algorithm. Finally, two example simulations verify the effectiveness of the optimization method in this paper and provide a certain theoretical basis for maintenance personnel to optimize decision-making.

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A genetic algorithm for scheduling multimode resource-constrained project problem in the presence of preemptive resources

Cited by 6 publications

References 33 publications

Blockchain of Optimal Multiple Construction Projects Planning Under Probabilistic Arrival and Stochastic Durations

Blockchain of Optimal Multiple Construction Projects Planning Under Probabilistic Arrival and Stochastic Durations

A Genetic Algorithm Model for Human Resource Management Optimization in the Internet Marketing Era

Maintenance Personnel Optimization Model of Vehicle Equipment Based on Support Task

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