• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2007년도 추계 학술논문 발표대회
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• pp.109-113
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• 2007

This paper introduces a system, Simulation based Stochastic Markup Estimation System (S2ME), for estimating optimum markup for a project. The system was designed and implemented to better represent the real world system involved in construction bidding. The findings obtained from the analysis of existing assumptions used in the previous quantitative markup estimation methods were incorporated to improve the accuracy and predictability of the S2ME. The existing methods has four categories of assumption as follows; (1) The number of competitors and who is the competitors are known, (2) A typical competitor, who is fictitious, is assumed for easy computation, (3) the ratio of bid price against cost estimate (B/C) is assumed to follow normal distribution, (4) The deterministic output obtained from the probabilistic equation of existing models is assumed to be acceptable. However, these assumptions compromise the accuracy of prediction. In practice, the bidding patterns of the bidders are randomized in competitive bidding. To complement the lack of accuracy contributed by these assumptions, bidding project was randomly selected from the pool of bidding database in the simulation experiment. The probability to win the bid in the competitive bidding was computed using the profile of the competitors appeared in the selected bidding project record. The expected profit and probability to win the bid was calculated by selecting a bidding record randomly in an iteration of the simulation experiment under the assumption that the bidding pattern retained in historical bidding DB manifest revival. The existing computation, which is handled by means of deterministic procedure, were converted into stochastic model using simulation modeling and analysis technique as follows; (1) estimating the probability distribution functions of competitors' B/C which were obtained from historical bidding DB, (2) analyzing the sensitivity against the increment of markup using normal distribution and actual probability distribution estimated by distribution fitting, (3) estimating the maximum expected profit and optimum markup range. In the case study, the best fitted probability distribution function was estimated using the historical bidding DB retaining the competitors' bidding behavior so that the reliability was improved by estimating the output obtained from simulation experiment.

• 한국정보통신학회논문지
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• 제19권10호
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• pp.2500-2506
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• 2015

지휘ㆍ통제ㆍ통신 체계와 같이 보안이 요구되고, 새로운 기술을 적용하여 새롭게 개발되어야 하는 무기체계의 업체선정은 정성적 평가인 제안서평가를 주로 적용하고 있다. 제안서평가의 주요 문제는 평가자의 주관적 성향에 따라 선호도가 달라 평가위원 구성과 점수 성향에 따라 우선순위가 달라지고, 기술능력평가의 변별력 저하 시 입찰 가격에 의해 업체가 선정된다는 것이다. 따라서 평가자의 주관적 성향을 보정함과 동시에 변별력을 높일 수 있는 방법이 필요하다. 일반적으로 적용되는 표준화 방법은 평균과 편차를 일치시키는 방법이나, 제안서평가와 같이 평가대상이 소규모이고, 평가대상별 수준이 유사한 경우 적용이 제한되었다. 이에 따라 제안서평가에 적용 가능한 새로운 표준화방법을 제시하였다. 이 방법은 평가자의 점수가 아니라 평가대상의 우선순위를 보정하는 방법으로 기존 표준화방법보다 성능이 우수하였고, 원점수를 최대한 반영함으로써 변별력을 높일 수가 있었으며 특히 평가대상수가 소규모인 경우에 더욱 성능이 우수하였다.