Innovative Linear Formulation for Transportation Reconstruction Planning

作     者：El-Anwar, Omar Ye, Jin Orabi, Wallied 

作者机构：Univ Washington Dept Construct Management Seattle WA 98195 USA Cairo Univ Dept Struct Engn Giza 12316 Egypt Univ Washington Dept Ind & Syst Engn Seattle WA 98195 USA Florida Int Univ OHL Sch Construct Miami FL 33174 USA 

出 版 物：《JOURNAL OF COMPUTING IN CIVIL ENGINEERING》 (土木工程计算杂志)

年 卷 期：2016年第30卷第3期

页      面：04015048-04015048页

核心收录：

学科分类：08[工学] 0813[工学-建筑学] 0814[工学-土木工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Royalty Research Fund Award of the University of Washington 

主　　题：Transportation network reconstruction Post-disaster recovery Multi-objective optimization Mixed-integer linear programming Contractors assignment Linear formulation Reconstruction costs 

摘      要：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.