Using genetic algorithms in optimizing construction material delivery schedules

Georgy, M; Basily, Sameh Y.

doi:10.1108/14714170810846503

Cited by 19 publications

(7 citation statements)

References 24 publications

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“…For this purpose, combining the forecasting method with a simulation framework (e.g. the study of Georgy and Basily, 2008) is helpful which would be an interesting area for future research. Moreover, considering and quantifying the impact of substitute material on the output of the project is another area to be studied.…”

Section: Discussionmentioning

confidence: 99%

A flexible genetic algorithm-fuzzy regression approach for forecasting

Azadeh

Kalantari

Ahmadi

et al. 2019

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Purpose Construction materials comprise a major part of the total construction cost. Given the importance of bitumen as a fundamental material in construction projects, it is imperative to have an accurate forecast of its consumption in the planning and material sourcing phases on the project. This study aims to introduce a flexible genetic algorithm-fuzzy regression approach for forecasting the future bitumen consumption. Design/methodology/approach In the proposed approach, the parameter tuning process is performed on all parameters of genetic algorithm (GA), and the finest coefficients with minimum errors are identified. Moreover, the fuzzy regression (FR) model is used for estimation. Analysis of variance (ANOVA) is used for selecting among GA, FR or conventional regression (CR). To show the applicability of the proposed approach, Iran’s bitumen consumption data in the period of 1991-2006 are used as a case study. Findings Production, import, export, road construction and price are considered as the input data used in the present study. It was concluded that, among all the forecasting methods used in this study, GA was the best method for estimating. Practical implications The proposed approach outperforms the conventional forecasting methods for the case of bitumen which is a fundamental economic ingredient in road construction projects. This approach is flexible, in terms of amount and uncertainty of the input data, and can be easily adapted for forecasting other materials and in different construction projects. It can have important implications for the managers and policy makers in the construction market where accurate estimation of the raw material demand is crucial. Originality/value This is the first in this field introducing a flexible GA-FR approach for improving bitumen consumption estimation in the construction literature. The proposed approach’s significance has two folds. Firstly, it is completely flexible. Secondly, it uses CRs as an alternative approach for estimation because of its dynamic structure.

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Section: Discussionmentioning

confidence: 99%

A flexible genetic algorithm-fuzzy regression approach for forecasting

Azadeh

Kalantari

Ahmadi

et al. 2019

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“…Tserng et al [31] introduced the Vendor Managed Inventory (VMI) philosophy into construction projects and developed a model minimizing the integrated inventory cost of the supply chain. Georgy and Basily [32] developed a computerized tool for optimizing the delivery and inventory of materials, as part of a comprehensive material management system in construction-projects. Xu et al [33] considered the recurrent projects with random material delays, and developed an integrated approach to jointly optimize material safety stock and project crashing decisions.…”

Section: Literature Reviewmentioning

confidence: 99%

Incentive schemes for centralized material planning and allocation with asymmetric information in construction supply chain

Wang

Chen

et al. 2024

IEEE Access

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In construction projects, a centralized management mode can effectively address the material management issues. Specifically, the Material Management Department (MMD) is responsible for material purchase, storage, and allocation based on the demand information reported by contractors. However, material demand are best observed by the contractors. They may manipulate the material takeoff (i.e. misrepresent the material demand) to increase the expected material allocation and avoid the project delay. Motivated by this situation, this paper focuses on the incentives to elicit truthful reporting from contractors. Cases of having prior information and no prior information about the material takeoff, as well as priority allocation and proportional allocation policies are considered. Under the case of having prior information, an incentive scheme is designed based on the Groves payment rule, while under the case of no prior information, two incentive schemes are designed based on the proper scoring rules. The comparison and numerical analysis show that the total three incentive schemes can induce the MMD to choose a systemoptimal inventory plan, as well as satisfy the participation constraints of contractors. Besides, the results also demonstrate that prior information is only the prerequisite for implementing the Groves incentive scheme and cannot improve the performance of the whole system in other aspects. INDEX TERMS Construction supply chain, material management, information asymmetry, incentive scheme. HUI LU received the B.Sc. degree in mechatronic engineering from Huazhong Agriculture University, and the Ph.D. degree in systems engineering from the

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“…Appropriate criteria are needed to be considered in selecting material location. Based on reviews of previous studies, the criteria are security (Proverbs et al, 1999), ability to recover temporary road (Koushki andKartam, 2004 andGeorgy andBasily, 2008), ability to support project schedule (Bakry et al, 2016 andKoushki andKartam, 2004), protection of social environment (Teriö et al, 2014), initial cost (Shakantu et al, 2003) and life cycle cost (LCC) of the materials (Fang and Ng, 2011). These criteria are used to construct the decision model for material location selection.…”

Section: Site Materials Selection and Decisionmentioning

confidence: 99%

Agreement options for negotiation on material location decision of housing development

Utomo

Rahmawati

2020

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Purpose Different housing development stakeholders need to cooperate and collaborate to perform various project activities. Housing development requires infrastructure development, which includes preparation of sand material embankment as much as ± 200,000 m3. The objectives are to find a model for agreement options and coalition, to validate the algorithms of the best fit for material locations and to determine how much the proposed agreement option was achieved. This study provides a structured methodology that can lead to systematic support system and automated negotiation for decision-making on housing development process. Design/methodology/approach Agreement option on group decision techniques was applied to determine the relative value of the alternative solutions for performing the function of project solutions. Analytical hierarchy process based on satisficing option was applied for decision process and game theory-based agent system for coalition formation. It is conducted in two stages that determine the decision preference and decision process consisting of four steps. The steps are constructing decision hierarchy, making judgment and synthesis, determining payoff optimum and analyzing the best fit option for all decision-makers. Findings The proposed model enables each decision-maker to select individually its coalition. It will improve the value of strategic decision. All solutions are chosen by more than one decision-maker and coalitions, where all decision-makers agree with the result. It becomes possible location for the material of a housing development. A support model enables negotiation process in group decision. Decision algorithms are based on the cooperative game theory to develop the agreement options and coalition formation. Similar research studies were carried out in this area, but this research is – to the knowledge of the authors – the first to apply the satisficing of value-based on desirable and considerable. Research limitations/implications The result is limited to the first-round negotiation of collaborative decision. A trade-off algorithm among decision-maker preference is needed for negotiation process. Future research is to continue working on multi-attribute decision-making, specifically on the process of eliciting user preference models such as neural network application and value function, and on establishing expert quantitative data from qualitative description of the feature of the alternative solution. It will need the development of trade-off algorithms to analyze value of technical solution in real time. Practical implications The support model can be extended to an automated negotiation and in different strategic decision on all stages of housing development. Social implications The satisficing algorithm of the coalition will satisfy all stakeholders. This will reduce any potential conflict. Originality/value Combination of value-based decision, group decision and collaborative support. Application of coalition formation for agreement options is used to select the best fit material location. It is based on satisficing game theory rather than optimization.

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Using genetic algorithms in optimizing construction material delivery schedules

Cited by 19 publications

References 24 publications

A flexible genetic algorithm-fuzzy regression approach for forecasting

A flexible genetic algorithm-fuzzy regression approach for forecasting

Incentive schemes for centralized material planning and allocation with asymmetric information in construction supply chain

Agreement options for negotiation on material location decision of housing development

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