1985Journal of Construction Engineering and ManagementRequires access

Decisions in Construction Operations

Bilal M. Ayyub, Achintya Haldar

Open publisher page 31 citations

Abstract

A method for selecting the most desirable construction strategy is proposed in this paper. A decision analysis framework is developed considering the information on relative risk, along with the information on cost, benefit, and consequences of each construction strategy. Many factors affect the safety of construction operations. Labor skill, supervisors' experience and attendance, condition of falsework, weather conditions, type of equipment, level of operator's experience, etc., may be considered as the main factors that affect the safety of construction operations. From an engineering point of view, these factors are always desirable to be in their best states. However, it may not be practical in many cases due to time and money constraints. Consequently, the risk of failure and cost of construction operations, and the consequences of failure need to be estimated in order to decide about the optimum construction strategy. The decision problem is complicated since the state of the factors are generally expressed in linguistic terms. The theory of fuzzy sets is used to translate these terms into mathematical measures and to estimate the risk of failure. The proposed method is illustrated with the help of an example.

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What this paper is about

A method for selecting the most desirable construction strategy is proposed in this paper. A decision analysis framework is developed considering the information on relative risk, along with the information on cost, benefit, and consequences of each construction strategy. Many factors affect the safety of construction operations. Labor skill, supervisors' experience and attendance, condition of falsework, weather conditions, type of equipment, level of operator's experience, etc., may be considered as the main factors that affect the safety of construction operations. From an engineering point of view, these factors are always desirable to be in their best states. However, it may not be practical in many cases due to time and money constraints. Consequently, the risk of failure and cost of construction operations, and the consequences of failure need to be estimated in order to decide about the optimum construction strategy. The decision problem is complicated since the state of the factors are generally expressed in linguistic terms. The theory of fuzzy sets is used to translate these terms into mathematical measures and to estimate the risk of failure. The proposed method is illustrated with the help of an example.

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Available abstract

A method for selecting the most desirable construction strategy is proposed in this paper. A decision analysis framework is developed considering the information on relative risk, along with the information on cost, benefit, and consequences of each construction strategy. Many factors affect the safety of construction operations. Labor skill, supervisors' experience and attendance, condition of falsework, weather conditions, type of equipment, level of operator's experience, etc., may be considered as the main factors that affect the safety of construction operations. From an engineering point of view, these factors are always desirable to be in their best states. However, it may not be practical in many cases due to time and money constraints. Consequently, the risk of failure and cost of construction operations, and the consequences of failure need to be estimated in order to decide about the optimum construction strategy. The decision problem is complicated since the state of the factors are generally expressed in linguistic terms. The theory of fuzzy sets is used to translate these terms into mathematical measures and to estimate the risk of failure. The proposed method is illustrated with the help of an example.

Key concepts: Risk analysis (engineering), Order (exchange), Operator (biology), Point (geometry), Computer science, Affect (linguistics), Operations research, Engineering

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