TY - GEN
T1 - Green vehicle routing problem with heterogeneous fleet and time windows
AU - Komarudin, null
AU - Gui, Robin
AU - Destyanto, Arry Rahmawan
N1 - Publisher Copyright:
© 2017 ACM.
PY - 2017/2/26
Y1 - 2017/2/26
N2 - The problem considered in this paper is to construct several routes and schedules of fleets that minimize the emission of a network consists of customers as nodes and their connection one to another by arcs, while varying the types of fleets and tightening the time windows. In the constructed models, the route of each fleet will be produced and treated as decision variable. The routes themselves depend on the capacity of each vehicle type and time windows constraints on each route. The objective of this paper is to construct routes of heterogeneous fleet problem with time windows with minimum emission, CO2eq in this context. A hybrid algorithm is used to construct the route. This algorithm is then validated using real demand historical data of a market in London. The result from model then used to analyze the differences which created by the algorithm and translated into a group of routes to be used.
AB - The problem considered in this paper is to construct several routes and schedules of fleets that minimize the emission of a network consists of customers as nodes and their connection one to another by arcs, while varying the types of fleets and tightening the time windows. In the constructed models, the route of each fleet will be produced and treated as decision variable. The routes themselves depend on the capacity of each vehicle type and time windows constraints on each route. The objective of this paper is to construct routes of heterogeneous fleet problem with time windows with minimum emission, CO2eq in this context. A hybrid algorithm is used to construct the route. This algorithm is then validated using real demand historical data of a market in London. The result from model then used to analyze the differences which created by the algorithm and translated into a group of routes to be used.
KW - Fuel emission optimization
KW - Green vehicle routing problem
KW - Tabu search algorithm
KW - Transportation
UR - http://www.scopus.com/inward/record.url?scp=85019488310&partnerID=8YFLogxK
U2 - 10.1145/3056662.3056714
DO - 10.1145/3056662.3056714
M3 - Conference contribution
AN - SCOPUS:85019488310
T3 - ACM International Conference Proceeding Series
SP - 223
EP - 227
BT - Proceedings of 2017 6th International Conference on Software and Computer Applications, ICSCA 2017
PB - Association for Computing Machinery
T2 - 6th International Conference on Software and Computer Applications, ICSCA 2017
Y2 - 26 February 2017 through 28 February 2017
ER -