In recent decades, construction project scheduling optimization has received extensive attention from the research community. However, the most commonly used scheduling approach, the critical path method, is often inapplicable to transportation-type linear projects. Recently, the linear scheduling method (LSM) has demonstrated many advantages for such projects and has become a popular research subject. As a relatively novel scheduling method, LSM requires further improvement, as there are restrictions associated with the scheduling/optimization of linear projects. By analyzing results from previous studies, we propose a unique three-element mode, a description method for LSM's logical relationships and constraints system. An LSM-based scheduling optimization model based on constraint satisfaction problems and constraint programming is then proposed that could be used in classical scheduling optimization problems with flexibility, practicability, and solution superiority. The proposed model is verified using three practical transportation construction projects. Verification under six optimization scenarios demonstrates the advantages of our approach.
Competitive bidding is the main mechanism of allocating projects in the construction market. In the traditional single criterion bidding method, the markup decision has a significant impact on a contractor's business success. Contractors usually take into consideration several factors in the process of determining their markup. This study has reviewed the literature and identified a range of contractors' behaviors when making their markup decision within a competitive bidding environment. An additive markup function consisting of three components, namely competition, risk, and need for work, was developed in order to replicate markup behaviors of contractors. Then, agent-based modeling has been employed for simulating the bidding process within a market formed of a set of heterogeneous contractors with different risk attitudes and defined markup behaviors. This model was used to study the impact of considering need for work and risk allowance in markup determination on financial performance of contractors in various market scenarios. Results suggest that the optimal policy is moderation in both dimensions of risk attitude and need for work.
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