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A hybrid mathematical programming model and statistical approach for bidding price decision in construction projects

机译:建设项目招标价格决策的混合数学规划模型及统计方法

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Bidding price decision is a key issue for the contractors and construction companies. The success/failure of the contractors in competitive biddings is directly dependent on their bidding strategy. This paper aims to develop a hybrid statistical and mathematical modeling approach for determining the optimum bidding price in construction projects. By statistical analysis of historical data, some uncertain parameters like the number of competitors and the cost of the project are estimated. Then, a scenario-based mathematical model for bidding price decision is proposed. In order to present a model in more accordance with the real-world situations, factors like risk, minimum acceptable rate of return (MARR) and opportunistic behavior are taken into account. In order to achieve an insensitive solution to the change in the realization of the input data from the scenarios, a robust mathematical model is used. The performance of the model is evaluated through some numerical problems. Furthermore, sensitivity analysis of the key parameters and robustness evaluation of the model against uncertain parameters are conducted. To evaluate the model's effectiveness in real-world situations, a case study is analyzed by the proposed approach. Numerical results show that the proposed approach reduces the cost estimation errors and increases the average expected profit, which validates the applicability of the model in a real-world situation.
机译:竞标价格决定是承包商和建筑公司的关键问题。竞争竞标者承包商的成功/失败直接依赖于竞标策略。本文旨在开发混合统计和数学建模方法,用于确定建筑项目中最佳竞标价格。通过统计分析历史数据,估计了一些不确定的参数,如竞争对手的数量和项目的成本。然后,提出了一种用于竞标价格决定的基于场景的数学模型。为了更加符合现实世界的情况来提出模型,考虑到风险等因素,最低可接受的回报率(Marr)和机会主义行为。为了实现对来自场景实现输入数据的变化的不敏感的解决方案,使用了一种稳健的数学模型。通过一些数值问题评估模型的性能。此外,进行了对不确定参数模型的关键参数和鲁棒性评估的灵敏度分析。为了评估模型在现实世界中的效果,通过所提出的方法分析了案例研究。数值结果表明,该方法降低了成本估计误差并增加了平均预期利润,验证了模型在真实情况下的适用性。

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