Human-in-the-Loop Decision Support for Disruption Management in Intermodal Bulk Logistics
Overview
| Company Name / Department |
Van den Bosch |
| Contact Person |
Anne Poot |
| Location |
Erp, The Netherlands |
| Optional remote work |
Hybrid working can be discussed depending on project setup and supervision needs. |
| Travel expenses (own account or reimbursed by the company) |
Reimbursed for travels > 10 km. |
| Housing arranged by company |
No
|
| Housing expenses (how much per month, own account or subsidized by the company) | Not applicable |
| Internship compensation | € 500 per month |
| Study program |
Primarily suitable for MSc Operations Management and Logistics, MSc Data Science and Artificial Intelligence, and MSc Artificial Intelligence and Engineering Systems |
| Start date | September 2026 |
Company Description
Van den Bosch is an international logistics service provider specializing in bulk logistics for the food and chemicals industries. The company operates intermodal supply chains using road, rail and sea transport and increasingly positions itself as a data- and insight-driven supply chain partner.
This environment creates a strong context for research into operational planning, disruption management, decision support, optimization, and AI-enabled logistics support.
Project Description
In daily operations, planners at Van den Bosch are confronted with disruptions that can invalidate an existing transport plan. Examples include delayed or cancelled barge or rail departures; trucks arriving too late due to previous assignments, or other disruptions that cause cascading effects elsewhere in the planning. These situations require planners to quickly assess alternatives and restore realistic and feasible planning, often under time pressure and with incomplete information.
The objective of this thesis is not to build a fully autonomous planning engine. Instead, the goal is to design and evaluate a human-in-the-loop decision-support solution that helps planners respond to disruptions more effectively. The solution should identify feasible alternatives, assess their likely consequences, and support the planner in selecting the most suitable response given operational constraints and business priorities.
Goal of the Project
The project should aim to:
- Identify the most relevant disruption types in Van den Bosch’s intermodal planning operations.
- Analyze how planners currently respond to disruptions and what constraints, trade-offs and heuristics they use.
- Map how disruptions affect other legs, resources, orders, or commitments in the planning network.
- Determine which data is needed to assess feasible and effective response options.
- Design and develop a practical decision-support artefact, such as a simulation model, optimization model, AI-supported ranking model or prototype tool.
- Evaluate the artefact on realistic scenarios using criteria such as feasibility, cost impact, delay reduction, service impact, robustness, and planner usefulness.
- Provide implementation recommendations for future use within Van den Bosch operations.
Deliverables
The thesis is expected to produce:
- A structured analysis of disruption types and their impact on operational planning.
- A decision framework for assessing replanning alternatives in an intermodal logistics setting.
- A practical artefact, such as a simulation, optimization model, AI-supported recommendation model, or prototype planner support tool.
- A scenario-based evaluation showing the impact of the proposed solution on operational KPIs.
- Recommendations for implementation, integration, and further development within Van den Bosch
Essential student knowledge
Depending on the student’s background, relevant knowledge may include operations research, optimization, simulation, machine learning, data analysis, process modelling, human-centered decision support, and an interest in logistics operations.
More information: escf@tue.nl
