TY  - CONF
CY  - Cairo
AV  - none
KW  - Ant Colony Optimization algorithms; Ant colony systems; Ant-colony optimization; Capacitated vehicle routing problem; Capacitated Vehicle Routing Problem (CVRP); Data sets; Optimization algorithms; Optimum solution; Other algorithms; Transportation industry; Vehicle routing problem
KW  -  Artificial intelligence; Information science; Routing algorithms; Vehicles
KW  -  Traveling salesman problem
ID  - scholars1228
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-77953155946&partnerID=40&md5=ea814fed95aa9c2e122d7e3468bba159
N1  - cited By 1; Conference of 2010 7th International Conference on Informatics and Systems, INFOS2010 ; Conference Date: 28 March 2010 Through 30 March 2010; Conference Code:80496
Y1  - 2010///
A1  - Rais, H.Md.
A1  - Othman, Z.A.
A1  - Hamdan, A.R.
N2  - Ant Colony System (ACS) is a well known optimization algorithm to find a good route solution for logistics and transportation industries such as Traveling Salesman Problem (TSP) or Vehicle Routing Problem (VRP), for the company maximize the efficiency and resource. Several versions of Ant Colony Optimization (ACO) algorithms have been proposed which aim to achieve an optimum solution includes Dynamic Ant Colony System with Three Level Updates (DACS3). DACS3 is an enhancement of ACS which focuses on adding individual ant behavior. The algorithm works better in TSP solution. This research aims to see the performance of DACS3 in VRP domain. The result shows that DACS3 has achieved a better solution for most the datasets of Capacitated Vehicle Routing Problem (CVRP). Embedding a simple behavior of a single ant influences its achievement to reach an optimal distance and also can perform considerably faster compare to other algorithm in TSP and CVRP.
TI  - Applying DACS3 in the capacitated vehicle routing problem
SN  - 9789774033964
ER  -