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Capacitate?d traffic assignment problem subject to variable demand, a nonlinear formulation cum solution code in GAMS Saeed Asadi Bagloee1, Majid Sarvi 1 1Smart Cities Transport Group, Department of Infrastructure Engineering, Melbourne School of Engineering, The University of Melbourne, Victoria 3010, Australia Email for correspondence: saeed.bagloee@.au Abstract Despite many realistic features represented by capacity constraints in traffic assignment problem (TAP), they are largely overlooked due to the inherent mathematical complexities. Extension of the conventional traffic assignment to elastic demand is also found widely missing. To overcome such complexities, we build on the work of (Ferris et al., 1999) and add side constraints to explicitly consider the physical capacity of the roads. The main advantage of this formulation over the past studies in the literature is to obviate any need for introducing additional parameter(s). The capacitated TAP is formulated and solved in GAMS and it is applied to the benchmark networks of Sioux-Falls and Melbourne CBD. Though GAMS is not necessarily a customized program for the TAP and computation time for large sized networks might be a concern, there exists a convincing argument in favour of GAMS: GAMS and its associated solvers can be effectively utilized in transportation planning when solving a (capacitated) TAP as a sub-problem is always inevitable. The network design (road extension decisions) and road pricing are of such practical problems which are known to be extremely difficult. To this ends, GAMS offers effective modules/methods such as, mpec module (mathematical programming with equilibrium constraint), mixed complementarity problem (mcp). 1. Introduction Finding traffic flow on a network for a given origin-destination travel demand is called Traffic Assignment Problem (TAP). The TAP is widely formulated based on the Wardrop principals to ensure that commuters seek least cost or shortest paths. This leads t