Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Genetic Algorithm‐Simulation Methodology for Pavement Maintenance Scheduling
Abstract: Pavement maintenance activities often involve lane closures, leading to traffic congestion and causing increases in road users' travel times. Scheduling of such activities should minimize the increases in travel times to all the travelers at network level. This article presents a hybrid methodology for scheduling of pavement maintenance activities involving lane closure in a network consisting of freeways and arterials, using genetic algorithm (GA) as an optimization technique, coupled with a traffic‐simulation model to estimate the total travel time of road users in the road network. The application of this scheduling method is demonstrated through a hypothetical problem consisting of assigning three maintenance teams to handle 10 job requests in a network in 1 day. After 10 generations of genetic evolution with a population size of four, the hybrid GA‐simulation model recommended a schedule that reduced the network total travel time by 5.1%, compared to the initial solution.
Genetic Algorithm‐Simulation Methodology for Pavement Maintenance Scheduling
Abstract: Pavement maintenance activities often involve lane closures, leading to traffic congestion and causing increases in road users' travel times. Scheduling of such activities should minimize the increases in travel times to all the travelers at network level. This article presents a hybrid methodology for scheduling of pavement maintenance activities involving lane closure in a network consisting of freeways and arterials, using genetic algorithm (GA) as an optimization technique, coupled with a traffic‐simulation model to estimate the total travel time of road users in the road network. The application of this scheduling method is demonstrated through a hypothetical problem consisting of assigning three maintenance teams to handle 10 job requests in a network in 1 day. After 10 generations of genetic evolution with a population size of four, the hybrid GA‐simulation model recommended a schedule that reduced the network total travel time by 5.1%, compared to the initial solution.
Genetic Algorithm‐Simulation Methodology for Pavement Maintenance Scheduling
Cheu, Ruey Long (Autor:in) / Wang, Ying (Autor:in) / Fwa, Tien Fang (Autor:in)
Computer‐Aided Civil and Infrastructure Engineering ; 19 ; 446-455
01.11.2004
10 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Genetic Algorithm-Simulation Methodology for Pavement Maintenance Scheduling
| Online Contents | 2004
A combined optimization-simulation methodology for pavement maintenance
| British Library Conference Proceedings | 2006
Genetic Algorithm Based Methodology for Optimal Maintenance Scheduling of Multi-Unit Systems
| British Library Online Contents | 2011
Multiyear Pavement Repair Scheduling Optimization by Preconstrained Genetic Algorithm
| British Library Conference Proceedings | 2002
Multiyear Pavement Repair Scheduling Optimization by Preconstrained Genetic Algorithm
| British Library Online Contents | 2002