Path: Top -> Journal -> Telkomnika -> 2015 -> Vol 13, No 2: June
An Ant Colony-based Heuristic Algorithm for Joint Scheduling of Post-earthquake Road Repair and Relief Distribution
An Ant Colony-based Heuristic Algorithm for Joint Scheduling of Post-earthquake Road Repair and Relief Distribution
Journal from gdlhub / 2016-11-17 02:56:36Oleh : Bei Xu, Yuanbin Song, Telkomnika
Dibuat : 2015-06-01, dengan 1 file
Keyword : Ant Colony Algorithm, Scheduling, Post-earthquake Response, Time-Space Network
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/1437
Emergency road repair and distribution of relief goods are crucial for post-earthquake response. However, interrelationships between those two tasks are not adequately considered in their work schedules, especially in cases with very limited repair resources, leading to unnecessary delay and expenditure. A time-space network model is constructed to better describe the constraints arising from the interrelationships in joint scheduling of road repair and relief distribution works. An ant colony-based heuristic algorithm is developed to solve the NP-hard model efficiently for practical use, followed by a case study of Wenchuan earthquake to validate the planning tool and to demonstrate its feasibility for resolving real world problem.
Deskripsi Alternatif :Emergency road repair and distribution of relief goods are crucial for post-earthquake response. However, interrelationships between those two tasks are not adequately considered in their work schedules, especially in cases with very limited repair resources, leading to unnecessary delay and expenditure. A time-space network model is constructed to better describe the constraints arising from the interrelationships in joint scheduling of road repair and relief distribution works. An ant colony-based heuristic algorithm is developed to solve the NP-hard model efficiently for practical use, followed by a case study of Wenchuan earthquake to validate the planning tool and to demonstrate its feasibility for resolving real world problem.
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