Project scheduling and material ordering problem with storage space constraints

Zhang, Yan; Cui, Nanfang

doi:10.1016/j.autcon.2021.103796

Cited by 18 publications

(9 citation statements)

References 24 publications

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“…Due to its versatility and usability, the NSGA-II has become one of the standard approaches to solving various scheduling problems in the construction industry, which has been tested in different studies [16]. Some of the recent models in the construction scheduling which have been solved by NSGA-II focus on optimizing other important aspects along with the project makespan minimization, such as material procurement [17,18], crew planning [19], project prioritization [20], location and workspace congestion [21], as well as project financing [22]. Due to metaheuristics' efficiency in similar construction scheduling problems, we decided to apply the NSGA-II algorithm from the open-source framework pymoo [23] that allows customization of the algorithm to the user needs.…”

Section: Resilient Scheduling Frameworkmentioning

confidence: 99%

“…Designs 2022, 6, x FOR PEER REVIEW 4 of 19 [17,18], crew planning [19], project prioritization [20], location and workspace congestion [21], as well as project financing [22]. Due to metaheuristics' efficiency in similar construction scheduling problems, we decided to apply the NSGA-II algorithm from the opensource framework pymoo [23] that allows customization of the algorithm to the user needs.…”

Section: Resilient Scheduling Frameworkmentioning

confidence: 99%

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Application of a Genetic Algorithm for Proactive Resilient Scheduling in Construction Projects

Milat

Knezić

Sedlar

2022

Designs

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During the execution of construction projects, uncertain events, such as delays, prolongations and disruptions of project activities, have the potential to cause a significant deviation between the planned and realized state of a project. As a result, progress on important project objectives can decrease and this leads to critical delays as well as heavy profit loss. For this reason, we propose the implementation of the customized evolutionary algorithm to generate resilient baseline schedules which include a sufficient number of time floats to absorb the negative impact of uncertainty. This way, the baseline solution is searched as a trade-off between project duration, its final profit and the overall baseline stability. The proposed algorithm is applied to real construction project data and the results of the analysis suggest improved stability for resilient baseline schedules. Application of the genetic algorithm to solve the existing multi-objective problem enables practical implementation of new technologies and methods in construction management. Resilient baseline schedules can be used in an uncertain environment to achieve more accurate predictions and support decision making in the areas of construction scheduling and costing.

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Section: Resilient Scheduling Frameworkmentioning

confidence: 99%

Section: Resilient Scheduling Frameworkmentioning

confidence: 99%

Application of a Genetic Algorithm for Proactive Resilient Scheduling in Construction Projects

Milat

Knezić

Sedlar

2022

Designs

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“…Different accidents require different types and quantities of materials, and scholars proposed emergency material scheduling schemes based on logistics models. For example, Zhang et al [6] proposed material scheduling when oil spill accidents occurred in petrochemical enterprises; Zhang and Cui [7] proposed material scheduling model in limited space. However, the material dispatch scheme only is considered in special circumstances, and ignores the situation dominated by fire and poisoning accidents.…”

Section: Introductionmentioning

confidence: 99%

Optimization of enterprise emergency material dispatch considering the third-party emergency force

Jiang

Bingyuan

2023

Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022)

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The third-party emergency forces such as neighboring enterprises in the accident can improve the rescue efficiency and shorten the rescue time to ensure the production and property safety of the affected people as much as possible. This paper proposes an emergency material scheduling model taking time as the objective and considering the participation of multi-party emergency forces. The model can freely decide the type of materials to improve the rescue efficiency when the risk index of the accident point is satisfied. A real case illustrates the applicability of the proposed model. The result shows that the average arrival time of emergency supplies for corporate safety production accidents is 12.53 minutes, of which 89.13% of accidents can deliver supplies within 10 minutes. Daishan Fire Brigade and CNOOC (Zhoushan) are the main rescue partners for enterprises. In addition, foam trucks are given priority to be put into the rescue process. This study can provide a basis for enterprises to adjust the storage of materials and the government to supervise enterprises.

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“…They proposed a multi-objective mathematical model to determine scheduling and ordering decisions so that the total cost and environmental and social impacts were minimized. To face uncertainties in activity durations and their detrimental effects on the inventory system, Zhang and Cui ( 2021 ) presented a two-stage optimization model to obtain robust solutions. Their first stage determined a basic schedule to minimize the total cost, and then, the proactive decisions related to the project schedule and material ordering were made in the second stage.…”

Section: Introductionmentioning

confidence: 99%

Maximizing projects’ profitability, environmental score, and quality: a multi-project scheduling and material ordering problem

Habibi

Chakrabortty

Abbasi

2023

Environ Sci Pollut Res

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The proper trade-off between various project costs is often disregarded when planning projects. This leads to several detrimental effects, such as inaccurate planning and higher total cost, far more significant in a multi-project environment. To overcome this limitation, this study proposes a combined approach for the multi-project scheduling and material ordering problem (MPSMOP), which maintains the proper trade-off among various costs. Moreover, the environmental impact and project quality objectives are optimized alongside the economic criterion. The proposed methodology involves three stages: (a) quantifying the environmental performance of suppliers; (b) measuring the activities’ quality through the Construction Quality Assessment System approach; and (c) building and solving the mathematical model of the MPSMOP. The MPSMOP is modeled as a tri-objective optimization approach aiming to determine project scheduling and material ordering decisions so that the net present value, environmental score, and total quality of implemented projects are maximized simultaneously. As the proposed model comes into the nondeterministic polynomial optimization problem category, two powerful metaheuristics are customized and used to solve the problem. The efficiency of both algorithms was assessed on several datasets. The proposed framework is applied to railway construction projects in Iran as a case study, which presents the validity of the model and the decision-making options provided to managers.

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Project scheduling and material ordering problem with storage space constraints

Cited by 18 publications

References 24 publications

Application of a Genetic Algorithm for Proactive Resilient Scheduling in Construction Projects

Application of a Genetic Algorithm for Proactive Resilient Scheduling in Construction Projects

Optimization of enterprise emergency material dispatch considering the third-party emergency force

Maximizing projects’ profitability, environmental score, and quality: a multi-project scheduling and material ordering problem

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