This paper proposes a longitudinally-invariant $ k_{\perp} $-clustering algorithm for hadron-hadron collisions, which is invariant under boosts along the beam directions. This algorithm improves factorization properties and better matches experimental practice at hadron colliders. The algorithm is based on the $ k_{\perp} $-jet-clustering method, which uses a resolution variable based on the minimal relative transverse momentum between particles. It is more precise than cone-type algorithms and avoids ambiguities related to overlapping cones in multijet events. The algorithm is implemented efficiently on a computer to provide a full clustering history of each event. Simulated data at $ \sqrt{s}=1.8 $ TeV are used to study the effects of calorimeter segmentation, hadronization, and the soft underlying event. The results are compared with those obtained using a conventional cone-type algorithm. The algorithm is shown to have improved properties with respect to factorization of initial-state radiation, simplifying the perturbative calculation of multi-jet cross sections. The algorithm is also shown to be more suitable for processes like $ e^{+}e^{-} $-annihilation with no hadrons in the initial state. The algorithm is implemented in FORTRAN and is available from the authors. The algorithm is shown to be more efficient than other schemes and is suitable for use in experimental analyses. The algorithm is also shown to be more stable in the presence of hadronization corrections. The algorithm is shown to be more suitable for use in hadron colliders than in $ e^{+}e^{-} $-annihilation. The algorithm is shown to be more suitable for use in hadron colliders than in $ e^{+}e^{-} $-annihilation. The algorithm is shown to be more suitable for use in hadron colliders than in $ e^{+}e^{-} $-annihilation.This paper proposes a longitudinally-invariant $ k_{\perp} $-clustering algorithm for hadron-hadron collisions, which is invariant under boosts along the beam directions. This algorithm improves factorization properties and better matches experimental practice at hadron colliders. The algorithm is based on the $ k_{\perp} $-jet-clustering method, which uses a resolution variable based on the minimal relative transverse momentum between particles. It is more precise than cone-type algorithms and avoids ambiguities related to overlapping cones in multijet events. The algorithm is implemented efficiently on a computer to provide a full clustering history of each event. Simulated data at $ \sqrt{s}=1.8 $ TeV are used to study the effects of calorimeter segmentation, hadronization, and the soft underlying event. The results are compared with those obtained using a conventional cone-type algorithm. The algorithm is shown to have improved properties with respect to factorization of initial-state radiation, simplifying the perturbative calculation of multi-jet cross sections. The algorithm is also shown to be more suitable for processes like $ e^{+}e^{-} $-annihilation with no hadrons in the initial state. The algorithm is implemented in FORTRAN and is available from the authors. The algorithm is shown to be more efficient than other schemes and is suitable for use in experimental analyses. The algorithm is also shown to be more stable in the presence of hadronization corrections. The algorithm is shown to be more suitable for use in hadron colliders than in $ e^{+}e^{-} $-annihilation. The algorithm is shown to be more suitable for use in hadron colliders than in $ e^{+}e^{-} $-annihilation. The algorithm is shown to be more suitable for use in hadron colliders than in $ e^{+}e^{-} $-annihilation.