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TY  - THES
AU  - Theiß, Alina
TI  - Metaheuristic optimization for complex routing problems
PB  - Rheinisch-Westfälische Technische Hochschule Aachen
VL  - Dissertation
CY  - Aachen
M1  - RWTH-2025-07568
SP  - 1 Online-Ressource : Illustrationen
PY  - 2025
N1  - Veröffentlicht auf dem Publikationsserver der RWTH Aachen University
N1  - Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2025
AB  - Optimizing transportation systems has become essential for addressing today's logistics challenges. As global trade grows consistently and consumer expectations for faster and on-time deliveries rise, companies face increasing pressure to deliver quickly and cost-efficiently. This thesis addresses four routing problems: First, the single truck and trailer routing problem with satellite depots (STTRPSD), which can be used to model the problem of optimizing routes of mail carriers in the last mile delivery stage of a mail delivery network. Second, the vehicle routing problem with depot operation constraints (VRP-DOC), which additionally includes the assignment of households to mail carriers in the route planning and incorporates depot operations. Third, the angular-metric traveling salesman problem (ATSP) and the angular-distance-metric traveling salesman problem (ADTSP), relevant for minimizing sharp turns in the routing of heavy vehicles. Last, the capacitated team orienteering problem with time-dependent and piecewise-linear score functions (C-TOP-TDPLSF) often used in the context of customer-focused deliveries. To efficiently solve realistically sized instances of these NP-hard problems, we use metaheuristics like iterated local search or tabu search. Each heuristic is designed to incorporate problem specific features to enhance their performance. Extensive computational experiments show significant improvements compared to state-of-the-art algorithms from the literature and practices implemented in the real world. For the STTRPSD, we use its natural decomposition into subproblems in the design of our heuristic, that reduces the travel times of real-world solutions currently used in practice by our industry partner on average by approximately 2
LB  - PUB:(DE-HGF)11
DO  - DOI:10.18154/RWTH-2025-07568
UR  - https://publications.rwth-aachen.de/record/1017789
ER  -