Dynamic Programming for the Minimum Tour Duration Problem

Christian Tilk () and Stefan Irnich ()
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Christian Tilk: Gutenberg School of Management and Economics, Johannes Gutenberg University Mainz, D-55128 Mainz, Germany
Stefan Irnich: Gutenberg School of Management and Economics, Johannes Gutenberg University Mainz, D-55128 Mainz, Germany

Transportation Science, 2017, vol. 51, issue 2, 549-565

Abstract: The minimum tour duration problem (MTDP) is a variant of the traveling salesman problem with time windows, which consists of finding a time window-feasible Hamiltonian path minimizing the tour duration. We present a new effective dynamic programming (DP)-based approach for the MTDP. When solving the traveling salesman problem with time windows with DP, two independent resources are propagated along partial paths, one for costs and one for earliest arrival times. For dealing with tour duration minimization, we provide a new DP formulation with three resources for which effective dominance and bounding procedures are applicable. This is a nontrivial task because in the MTDP at least two resources depend on each other in a nonadditive and nonlinear way. In particular, we define consistent resource extension functions (REFs) so that dominance is straightforward using componentwise comparison for the respective resource vectors. Moreover, one of the main advantages of the new REF definition is that the DP can be reversed consistently such that the forward DP or any of its relaxations provide bounds for the backward DP, and vice versa. Computational tests confirm the effectiveness of the proposed approach.

Keywords: traveling salesman problem; time windows; tour duration; dynamic programming; state-space relaxation (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (13)

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