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Optimally solving a versatile Traveling Salesman Problem on tree networks with soft due dates and multiple congestion scenarios

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  • Bock, Stefan

Abstract

This paper considers a versatile Traveling Salesman Problem (TSP) on tree networks with soft due date restrictions. Data unreliability is handled by introducing multiple congestion scenarios. The objective function sums up customizable monotonous cost assessments of the scenario-dependent total tardiness. Due to its generality, this covers a versatile application of different concepts including several robustness issues. Various complexity results are derived for the minimization of total tardiness: While the problem is proven to be at least binary NP-hard in all cases, strongly NP-hardness is shown if either the number of congestion scenarios or the number of roads are allowed to increase linearly with the number of requests. The same applies if non-zero unloading times occur. In order to efficiently solve the problem, a best-first Branch&Bound approach is proposed that attains a pseudo-polynomial running time if none of the three aforementioned cases applies. The Branch&Bound approach is evaluated by a computational study.

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  • Bock, Stefan, 2020. "Optimally solving a versatile Traveling Salesman Problem on tree networks with soft due dates and multiple congestion scenarios," European Journal of Operational Research, Elsevier, vol. 283(3), pages 863-882.
    • Handle: RePEc:eee:ejores:v:283:y:2020:i:3:p:863-882
    DOI: 10.1016/j.ejor.2019.11.058
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