CONFERENCE




Special Session: Vehicle Routing Problem


A special session in the 1st International Conference on ARTIFICIAL INTELLIGENCE and COGNITIVE SCIENCE (AICS '13). 

Topics related to: Artificial Intelligence, Heuristic searching methods, Search and meta-heuristics, AI and evolutionary algorithms, Evolutionary computing.

The Vehicle Routing Problem (VRP) is a general combinatorial optimization problem that has become a key component of transportation management. The VRP was first introduced by Dantzig & Ramser in 1959. General VRP is defined on a connected graph G. Let G = (V, A) be a graph where V is a set of nodes (vertices) and A is the set of arcs (edges). Let C = (cij) be a cost matrix associated with A. The matrix C is said to be symmetric when cij = cji and asymmetric otherwise. The vehicle must start and finish its tour at the depot and the problem is to construct at minimum travel cost. VRP lies between travelling salesman problem (TSP) and the bin packing problem (BPP).

In combinatorial optimization, the TSP and the BPP are a NP-hard. The abbreviation NP-hard refers to nondeterministic polynomial time hard. That means that it is not guaranteed that there is a known algorithm that solves all cases to optimality in a reasonable execution time. So in addition of an appropriate solution approach, a number of heuristics and meta-heuristics have been developed to find a solution to the problem.

Organized in collaboration with:
The Technical University of Sofia (Bulgaria)
Polytechnic University of Bari (Italy)
University Politehnica of Bucharest (Romania)

More details, please visit official website at

Important Dates
Abstract Submission: 31 October 2013
Acceptance of the abstract: 15 December 2013
Deadline for submitting the full paper (optional) and early payment: 28 February 2014
Acceptance of the full paper: 31 March 2014
4-6 June 2014 - Kos Island, Greece


If you have any inquiries or suggestions, please feel free to contact us:
ariel.ismail@siswa.um.edu.my
ariel.ismail.let@gmail.com









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