  We consider a continuous supply chain network consisting of buffering queues
and processors first proposed by [D. Armbruster, P. Degond, and C. Ringhofer,
SIAM J. Appl. Math., 66 (2006), pp. 896--920] and subsequently analyzed by [D.
Armbruster, P. Degond, and C. Ringhofer, Bull. Inst. Math. Acad. Sin. (N.S.), 2
(2007), pp. 433--460] and [D. Armbruster, C. De Beer, M. Freitag, T. Jagalski,
and C. Ringhofer, Phys. A, 363 (2006), pp. 104--114]. A model was proposed for
such a network by [S. G\"ottlich, M. Herty, and A. Klar, Commun. Math. Sci., 3
(2005), pp. 545--559] using a system of coupling ordinary differential
equations and partial differential equations. In this article, we propose an
alternative approach based on a variational method to formulate the network
dynamics. We also derive, based on the variational method, a computational
algorithm that guarantees numerical stability, allows for rigorous error
estimates, and facilitates efficient computations. A class of network flow
optimization problems are formulated as mixed integer programs (MIPs). The
proposed numerical algorithm and the corresponding MIP are compared
theoretically and numerically with existing ones [A. F\"ugenschuh, S.
G\"ottlich, M. Herty, A. Klar, and A. Martin, SIAM J. Sci. Comput., 30 (2008),
pp. 1490--1507; S. G\"ottlich, M. Herty, and A. Klar, Commun. Math. Sci., 3
(2005), pp. 545--559], which demonstrates the modeling and computational
advantages of the variational approach.
