El-Anwar, Omar; Ye, Jin; Orabi, Wallied. (2016). Innovative Linear Formulation for Transportation Reconstruction Planning. Journal Of Computing In Civil Engineering, 30(3).
Abstract
Following disasters, the pace of restoring transportation networks can have a significant impact on economic and societal recovery. However, reconstruction and repair efforts are typically faced by budget constraints that require careful selection among competing contractors. This paper presents an innovative formulation to optimize this complex planning problem in order to maximize the rate of transportation network recovery while minimizing the associated reconstruction costs. This study first contributes to the body of knowledge by offering an effective and efficient means of identifying the optimal schedules for reconstruction projects and the optimal contractor assignments. This is achieved by solving the problem using a new mixed-integer linear programming model. However, there are four main formulation challenges to represent this problem using linear equations because of the need to use logical operators. As such, the second contribution of this study is in offering innovative solutions to overcome these formulation challenges, which are generalizable to other construction scheduling and planning problems. This paper is companion to another paper that describes a holistic optimization and traffic assessment methodology for post-disaster reconstruction planning for damaged transportation networks. (C) 2015 American Society of Civil Engineers.
Keywords
Integer Programming; Linear Programming; Transportation; Innovative Linear Formulation; Transportation Reconstruction Planning; Economic Recovery; Societal Recovery; Complex Planning Problem; Transportation Network Recovery; Mixed-integer Linear Programming Model; Traffic Assessment Methodology; Postdisaster Reconstruction Planning; Natural Disasters; Housing Projects; Construction; Optimization; Performance; Robustness; Earthquake; Efficiency; Recovery; Plans; Transportation Network Reconstruction; Post-disaster Recovery; Multi-objective Optimization; Mixed-integer Linear Programming; Contractors Assignment; Linear Formulation; Reconstruction Costs