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A multi-objective decision-support model for selecting environmentally conscious highway construction methods

    Gulbin Ozcan-Deniz Affiliation
    ; Yimin Zhu Affiliation

Abstract

The construction industry has a considerable share in overall resource and energy consumption. Consequently, decision-makers try to achieve environmentally conscious construction by integrating environmental objectives into the selection of construction elements. Due to the complexity of construction projects, it is a known challenge to provide an effective mechanism to select the most feasible construction methods. Thus, it is crucial to learn the interdependency between various resource alternatives, such as material and equipment type, under various project conditions like unavailability of resources. An analytic network process (ANP) was used in this study to construct a decision model for selecting the most feasible construction method. Data collected via interviews with highway construction experts were used to model the dependency between decision parameters, such as project conditions and resource performance indicators. The proposed ANP model output the relative importance weights of decision parameters so that they can be used to identify environmentally conscious construction methods. The proposed mechanism is a valuable asset for construction decision-makers especially when their ability to select construction methods is limited by project constraints. Although the model was tested in a highway project in this paper, it can be further extended to benefit building construction and sustainable decision-making problems.

Keyword : sustainable construction, analytic network process, highway construction, construction methods, multi-criteria decision-making

How to Cite
Ozcan-Deniz, G., & Zhu, Y. (2015). A multi-objective decision-support model for selecting environmentally conscious highway construction methods. Journal of Civil Engineering and Management, 21(6), 733-747. https://doi.org/10.3846/13923730.2014.893915
Published in Issue
Jun 9, 2015
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