The bid/no bid decision is an important and complex process, and is impacted by numerous variables that are related to the contractor, project, client, competitors, tender and market conditions. Despite the complexity of bid decision making process, in the construction industry the majority of bid/no bid decisions is made informally based on experience, judgment, and perception. In this paper, a procedure based on support vector machines and backward elimination regression is presented for improving the existing bid decision making methods. The method takes advantage of the strong generalization properties of support vector machines and attempts to further enhance generalization performance by eliminating insignificant input variables. The method is implemented for bid/no bid decision making of offshore oil and gas platform fabrication projects to achieve a parsimonious support vector machine classifier. The performance of the support vector machine classifier is compared with the performances of the worth evaluation model, linear regression, and neural network classifiers. The results show that the support vector machine classifier outperforms existing methods significantly, and the proposed procedure provides a powerful tool for bid/no bid decision making. The results also reveal that elimination of the insignificant input variables improves generalization performance of the support vector machines.


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Arıkan, Ae; Dikmen Toker, İrem; Birgönül, Mustafa Talat (null; 2009-09-30)
Although risk management (RM) is accepted as one of the critical success factors for construction projects, project participants generally do not have sufficient knowledge pertinent to RM concept and the number of support tools which facilitate the process is rather low. Decision support tools are necessary for the systematic identification of risks, scenario generation, and proactive management of risk and integration of RM activities with other project management functions. The aim of this study is to int...
A Support vector regression method for conceptual cost estimate of construction projects
Yolasığmaz, İsmet Berki; Sönmez, Rifat; Department of Civil Engineering (2015)
Conceptual cost estimate is very important for initial project decisions when the design information is limited and the scope is not finalized at the early stages of the construction projects. It has serious effects on planning, design, cost management and budgeting. Therefore, the decision makers should be as accurate as possible while estimating the conceptual cost at the initial stage since a misestimation on the conceptual cost may lead to serious problems during feasibility analysis or at the later sta...
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In construction sector, deciding on building investment / refurbishments can be a complex process because it involves multiple criteria and generally conflicting objectives. For this reason, in the early phase, it is necessary to carry out an analysis that can enhance the predictability of these decisions taken, determine the optimum points of conflicting decisions and at the same time increase the social, environmental and economic sustainability. In the analysis, the total cost incurred building life cycl...
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Cihangir, Çiğdem; Bayındır, Zeynep Pelin; Tan, Tarkan; Department of Industrial Engineering (2010)
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The nature of construction projects is very iterative and there are various people involved from different disciplines and organizations in the process. Design stage is unique, complex and require combination and expertise of different people. The capture and reuse of design experience is considered as an efficient way to promote a better design process and efficient building solutions. The smallest part in a building is the space. It is a long-term asset of a building; therefore, a space knowledge manageme...
Citation Formats
R. Sönmez, “A SUPPORT VECTOR MACHINE METHOD FOR BID/NO BID DECISION MAKING,” JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT, pp. 641–649, 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/47330.