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Decision support for the operational planning phase of the transit network planning problem

Thesis (PhD)--Stellenbosch University, 2026.

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Main Author: Steenkamp, Pieter Jacobus
Other Authors: Van Vuuren, J. H.
Format: Thesis
Language:English
Published: Stellenbosch : Stellenbosch University 2026
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access_status_str Open Access
author Steenkamp, Pieter Jacobus
author2 Van Vuuren, J. H.
author_browse Steenkamp, Pieter Jacobus
Van Vuuren, J. H.
author_facet Van Vuuren, J. H.
Steenkamp, Pieter Jacobus
author_sort Steenkamp, Pieter Jacobus
collection Thesis
dc_rights_str_mv Stellenbosch University
description Thesis (PhD)--Stellenbosch University, 2026.
format Thesis
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institution Stellenbosch University (South Africa)
language English
last_indexed 2026-06-10T12:44:06.995Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository
publishDate 2026
publishDateRange 2026
publishDateSort 2026
publisher Stellenbosch : Stellenbosch University
publisherStr Stellenbosch : Stellenbosch University
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source_str SUNScholar — Stellenbosch University Repository
spelling oai:scholar.sun.ac.za:10019.1/135816 Decision support for the operational planning phase of the transit network planning problem Steenkamp, Pieter Jacobus Van Vuuren, J. H. Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering. Thesis (PhD)--Stellenbosch University, 2026. Steenkamp, P. J. 2026. Decision support for the operational planning phase of the transit network planning problem. Unpublished doctoral dissertation. Stellenbosch: Stellenbosch University [online]. Available: https://scholar.sun.ac.za/items/8308a90b-7a95-43c6-8258-289727898aa7 The planning problem underlying the design of a transit system is known in the literature as the transit network planning problem (TNPP). Due to the high degree of complexity of decisions pertaining to the transit network planning process, the TNPP has traditionally been partitioned into strategic, tactical, operational, and control phases. The operational planning phase of the TNPP requires the solution of complex, interdependent sub-problems, such as the vehicle scheduling problem (VSP), the crew scheduling problem (CSP), and the crew rostering problem (CRP). While various mathematical models are available for integrating these problems, the general failure to incorporate staff transportation requirements into these integrated models is a significant gap in the existing body of knowledge. This gap is addressed in the current dissertation by formally establishing a novel, integrated problem called the vehicle crew rostering problem with staff transportation (VCRPST). A novel decision support framework (DSF) is proposed in this dissertation for aiding planners during the operational planning phase of attempts at solving instances of the TNPP. The DSF is designed to provide a structured and adaptable guide for assisting transport planners with the complex decision-making processes involved in holistically integrating vehicle scheduling, crew scheduling, crew rostering, and staff transport decisions during the operational planning phase of the TNPP. The framework is modular in nature, and consists of a database component, a model component, a solution component, and a user-interface component. A novel mathematical model and an accompanying two-phase solution approach are proposed for the VCRPST. The mathematical model innovatively employs a time-space network representation to capture the interdependencies between vehicle and crew assignments over a multi-day rostering period. Recognising the computational intractability of this integrated model, the twophase solution approach involves first employing a column generation scheme to solve the daily VCSPST during a scheduling phase. The high-quality set of feasible duties generated during this first phase is then exploited to solve the full VCRPST model during a subsequent rostering phase. The framework and computerised implementations of its components are finally applied to three case studies involving real-world VCRPST data provided by an industry partner, in order to demonstrate the practical applicability of the dissertation contributions. The results demonstrate that the solutions generated by the DSF are capable of achieving significant operational improvements and cost savings over solutions produced by a manual scheduling process. Doctoral 2026-04-10T13:27:56Z 2026-04-10T13:27:56Z 2026-03 Thesis https://scholar.sun.ac.za/handle/10019.1/135816 en Stellenbosch University 225 pages application/pdf Stellenbosch : Stellenbosch University
spellingShingle Steenkamp, Pieter Jacobus
Decision support for the operational planning phase of the transit network planning problem
title Decision support for the operational planning phase of the transit network planning problem
title_full Decision support for the operational planning phase of the transit network planning problem
title_fullStr Decision support for the operational planning phase of the transit network planning problem
title_full_unstemmed Decision support for the operational planning phase of the transit network planning problem
title_short Decision support for the operational planning phase of the transit network planning problem
title_sort decision support for the operational planning phase of the transit network planning problem
url https://scholar.sun.ac.za/handle/10019.1/135816
work_keys_str_mv AT steenkamppieterjacobus decisionsupportfortheoperationalplanningphaseofthetransitnetworkplanningproblem