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J.H. Kwakkel

196 records found

Geopolitical tensions and conflicts can disrupt energy markets, threatening international energy supply security and imposing financial stress on energy-intensive industries reliant on imported fossil fuels. Exploring the challenges and opportunities associated with supply divers ...

Let decision-makers direct the search for robust solutions

An interactive framework for multiobjective robust optimization under deep uncertainty

The robust decision-making framework (RDM) has been extended to consider multiple objective functions and scenarios. However, the practical applications of these extensions are mostly limited to academic case studies. The main reasons are: (i) substantial cognitive load in tracki ...
Supply chain visibility concerns the ability to track parts, components, or products in transit from supplier to customer. The data that organizations can obtain to establish or improve supply chain visibility is often sparse. This paper presents a classification of the dimension ...
Simulation–optimization models are well-suited for real-time decision-support to the control room for search and interception of fugitives by Police on a road network, due to their ability to encode complex behavior while still optimizing the interception. The typical simulation– ...
Evolutionary Multi-Objective Direct Policy Search (EMODPS) is a prominent framework for designing control policies in multi-purpose environmental systems, combining direct policy search with multi-objective evolutionary algorithms (MOEAs) to identify Pareto approximate control po ...
Schedule design in the transportation and logistics sector is a widely studied problem. Transport service providers, such as the train industry and aviation, aim for schedules to be on-time according to the planning (i.e., on-time performance or OTP) in order to increase the serv ...
Adaptive pathways planning is an approach that maps the solution space over time to inform decision making under uncertainty. Since its first applications to climate change adaptation in the ’10s several studies and practical applications have used and extended the approach and d ...
Infrastructure in low-lying coastal areas faces challenges from climate change, sea level rise, and the impact of compound hazards. Dynamic adaptive pathways planning (DAPP) is increasingly being applied as a way of planning under deep uncertainty. Stress testing for robustness i ...
Tin is an important metal for society with a high risk of supply disruptions. It is, therefore, classified as a critical material in many parts of the world. An exception is the European Union, for which tin was classified as a non-critical material in 2023. However, there are ma ...
Illicit supply chains for products like counterfeit Personal Protective Equipment (PPE) are characterized by sparse data and great uncertainty about the operational and logistical structure, making criminal activities largely invisible to law enforcement and challenging to interv ...

Modeling with a municipality

Exploring robust policies to foster climate-neutral mobility

Many European cities are investigating how to transition to climate-neutral transport systems. Due to the transport system's complexity and uncertainty about the future, identifying drivers and choosing effective policies to make the city more sustainable is challenging. Addition ...
Mesopelagic fishes are a vital component of the biological carbon pump and are, to date, largely unexploited. In recent years, there has been an increased interest in harvesting the mesopelagic zone to produce fish feed for aquaculture. However, great uncertainties exist in how t ...

From past to future

Understanding urban development in flood-prone coastal Rome

This paper explores the spatial evolution of a flood-prone, sub-urban coastal area, Municipio X of Rome. The study investigates land use change through a diachronic analysis, providing empirical data to retrace the implication of the factors that shaped the study area and highlig ...
Integrated Assessment Models (IAMs) vary widely in complexity and underlying assumptions. There have been considerable efforts to increase the complexity of IAMs for improved representation of socioeconomic and environmental outcomes. However, less attention has been given to the ...

Exploring potential futures

Evaluating the influence of deep uncertainties in urban planning through scenario planning: A case study in Rome, Italy

Cities play a critical role in developing adaptable strategies to address the challenges posed by climate change. However, the inherent complexity of urban environments and their uncertain future conditions necessitate exploring innovative approaches and tools to assist the curre ...
Decision-making under uncertainty is important for managing human-natural systems in a changing world. A major source of uncertainty is linked to the multi-actor settings of decisions with poorly understood values, complex relationships, and conflicting management approaches. Des ...

Calibrating Simulation Models with Sparse Data

Counterfeit Supply Chains During Covid-19

COVID-19 related crimes like counterfeit Personal Protective Equipment (PPE) involve complex supply chains with partly unobservable behavior and sparse data, making it challenging to construct a reliable simulation model. Model calibration can help with this, as it is the process ...
To adapt to a changing climate, decision-makers design, evaluate, and implement measures that have an implication of justice on citizens in the present and well into the future. Decision-makers are often required to make decisions without certainty of the consequences and underst ...

Belief-Informed Robust Decision Making (BIRDM)

Assessing changes in decision robustness due to changing distributions of deep uncertainties

Robust Decision Making (RDM) is an established framework for decision making under deep uncertainty. RDM relies on the idea of scenario neutrality, namely that decision robustness is not affected by how scenarios are generated if these are uniformly distributed and span a suffici ...
Policy of Multi-Actor Systems is an introduction into the art of craft of problem exploration and problem structuring. It positions policy analysis as a scientific discipline focused on systems analysis in a multi-actor context to support better informed decision-making. The appr ...