Title :
Bin-packing multi-depots vehicle scheduling problem and its ant colony optimization
Author :
Wang, Suxin ; Wang, Leizhen ; Niu, Yanying ; Ge, Meng
Author_Institution :
Northeastern Univ. at Qinhuangdao, Qinhuangdao, China
Abstract :
In order to solve bin-packing multi-depots vehicle scheduling problem (BPMDVSP), BPMDVSP model bases on goods is established. A tabu matrix bases on goods is established for ant colony optimization (ACO). Matrix has three rows, first row corresponds to goods start depot visit state, second row corresponds to goods end depot visit state, and third row corresponds to vehicle that ferries the goods. Tabu matrix´s every column corresponds to goods, if goods qualities overload vehicle capacity, the goods column changes to goods bale numbers columns, and every column corresponds to a bale. The depot visit states in tabu matrix are set to avoid goods consignment mistake and single goods is ferried by different vehicles. State transfer rules are set when the two adjacent nodes are the same. According to ants tabu matrix, all the vehicle routs are searched by ants and satisfy the vehicle constrain. The illustration result shows model and algorithm can solve vehicle scheduling problem regardless goods whether in vehicle capacity.
Keywords :
bin packing; goods distribution; optimisation; scheduling; transportation; BPMDVSP model; ant colony optimization; bin-packing multidepots vehicle scheduling problem; goods bale numbers; goods consignment; goods end depot visit state; goods start depot visit state; state transfer rule; tabu matrix; vehicle capacity; vehicle rout; Ant colony optimization; Approximation algorithms; Automotive engineering; Educational institutions; Electronic mail; Gravity; Information science; Processor scheduling; Scheduling algorithm; Vehicles; Ant Colony Optimization; Bin-Packing Problem; Multi-Depots; Vehicle Scheduling Problem;
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
DOI :
10.1109/CCDC.2009.5191482