2026-09-21T06:03:10Z https://opus4.kobv.de/opus4-uni-passau/oai

oai:kobv.de-opus4-uni-passau:2090 2026-06-22 bibliography:false doc-type:PhDThesis open_access ddc ddc:006 ddc:330 ddc:519 ddc:604

Studies of Complex Routing Problems with Synchronization and Stochastic Information 0009-0009-7975-2865 Luis Aurelio Rocha 006 330 519 604 VRP PDP synchronization uncertainty specimen collection Routing problems typically assume deterministic parameters and independent vehicle operations. Many real-world logistics systems, however, involve synchronization requirements among resources and uncertainty in system parameters — challenges that are both practically relevant and theoretically difficult. This dissertation addresses both dimensions through a series of complementary contributions. We begin with a literature review of specimen logistics, surveying strategic, tactical, and operational routing problems in laboratory supply chains. We then develop a two-index formulation for the specimen collection problem with synchronized multiple trips and one lab, which solves 55 out of 56 small instances where the state-of-the-art model finds none, proves optimality in up to 30% of larger instances, and outperforms the state-of-the-art ALNS in 8 out of 12 settings with an average gap of 1.12%. In the third chapter, we introduce a compact model for the pickup-and-delivery problem with transfers, strengthened by novel valid inequalities, and extended to a novel branch-and-cut approach, which outperforms existing methods by solving 68 of 90 large benchmark instances and, for the first time, solves instances with up to 50 requests. The fourth chapter addresses a truck-and-drone TSP under vehicle synchronization and edge-traversal uncertainty in disaster relief settings; we derive competitive ratios for common policies, validate them in simulation, and propose an improved hybrid policy exploiting uncertainty through strategic surveillance. Finally, we study a production routing problem with stochastic driver availability. Our new deterministic heterogeneous-vehicle reformulation (HetPRP) outperforms our customized Benders decomposition approach, achieving average optimality gaps of 0.11%–0.97% on benchmark instances with up to 50 retailers and nine periods. We further quantify the value of stochastic solutions — up to 5.23% in non-urban settings — and show through a case study that integrating crowd-sourced drivers can yield cost savings of up to 21.71%. Taken together, these contributions advance the state of the art in synchronized and stochastic routing, offering both theoretical guarantees and practically efficient solution methods. Universität Passau Passau Innstrasse 29, 94032 Passau 0000-0002-6069-9330 Alena Otto 0000-0002-1671-0344 Frauke Liers 2026-04-22 2026-06-22 PhDThesis Text urn:nbn:de:bvb:739-opus4-20906 application/pdf eng Standardbedingung laut Einverständniserklärung thesis.doctoral Universität Passau Passau Wirtschaftswissenschaftliche Fakultät 1 https://opus4.kobv.de/opus4-uni-passau/oai/container/index/docId/2090 https://opus4.kobv.de/opus4-uni-passau/frontdoor/index/index/docId/2090