Journal
ENGINEERING STRUCTURES
Volume 117, Issue -, Pages 591-602Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.engstruct.2016.03.038
Keywords
Optimization; Scheduling; Evolutionary algorithms; Resilience; Bridge networks; Disaster management; AMIGO
Categories
Funding
- National Science Foundation [CMMI - 1541177]
- P.C. Rossin College of Engineering and Applied Science through the Rossin Doctoral Fellowship
- Department of Civil and Environmental Engineering
- ATLSS Engineering Research Center at Lehigh University
- Directorate For Engineering
- Div Of Civil, Mechanical, & Manufact Inn [1541177] Funding Source: National Science Foundation
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A novel evolutionary optimization methodology called Algorithm with Multiple-Input Genetic Operators (AMIGO) for scheduling independent tasks considering resource and time constraints is presented. AMIGO is characterized by new genetic operators enriched with complementary information, including auxiliary variables computed by the fitness function, as well as the global parameters of the problem. The application of AMIGO to multi-phase optimal resilience restoration scheduling of highway bridges is presented and discussed. To this purpose, enhancements have been made also to the bridge network resilience analysis (a new performance metric and restoration model). The quality of the solution and efficiency of AMIGO are demonstrated through the application to a large transportation network subjected to earthquake. (C) 2016 Elsevier Ltd. All rights reserved.
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