Buffer scheduling for improving on-time performance and connectivity with a multi-objective simulation–optimization model: A proof of concept for the airline industry

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 service level by ensuring that passengers actually make their...

Simulation–optimization configurations for real-time decision-making in fugitive interception

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–optimization configuration is simulation model optimization,...

Exploring global approximators for multiobjective reservoir control

Efficient multi-purpose reservoir control policies are crucial in the face of frequent and severe floods and droughts, and to balance water allocation across conflicting demands. Evolutionary Multi-Objective Direct Policy Search (EMODPS) is a popular approach to design control policies for multi-purpose reservoir systems. EMODPS, however, relies...

Multi-scenario multi-objective robust optimization under deep uncertainty: A posteriori approach

This paper proposes a novel optimization approach for multi-scenario multi-objective robust decision making, as well as an alternative way for scenario discovery and identifying vulnerable scenarios even before any solution generation. To demonstrate and test the novel approach, we use the classic shallow lake problem. We compare the results...

Is real options analysis fit for purpose in supporting climate adaptation planning and decision-making?

Even though real options analysis (ROA) is often thought as the best tool available for evaluating flexible strategies, there are profound problems with the assumptions underpinning ROA rendering it unsuitable for use in supporting planning and decision-making on climate adaptation. In the face of dynamic and deep uncertainty about the future...

On considering robustness in the search phase of Robust Decision Making: A comparison of Many-Objective Robust Decision Making, multi-scenario Many-Objective Robust Decision Making, and Many Objective Robust Optimization

In recent years, a family of approaches has emerged for supporting decision-making on complex environmental problems characterized by deep uncertainties and competing priorities. Many-Objective Robust Decision Making (MORDM), Multi-scenario MORDM and. Many-Objective Robust Optimization (MORO) differ with respect to the degree to which...

Accounting for the uncertain effects of hydraulic interactions in optimising embankments heights: Proof of principle for the IJssel River

Most alluvial plains in the world are protected by flood defences, for example, embankments, whose primary aim is to reduce the probability of flooding of the protected areas. At the same time, however, the presence of embankments at one area influences hydraulic conditions of downstream areas located on the same river. These hydraulic...

Including robustness considerations in the search phase of Many-Objective Robust Decision Making

Many-Objective Robust Decision Making (MORDM) is a prominent model-based approach for dealing with deep uncertainty. MORDM has four phases: a systems analytical problem formulation, a search phase to generate candidate solutions, a trade-off analysis where different strategies are compared across many objectives, and a scenario discovery...

Adaptive policymaking under deep uncertainty: Optimal preparedness for the next pandemic

The recent flu pandemic in 2009 caused a panic about the possible consequences due to deep uncertainty about an unknown virus. Overstock of vaccines or unnecessary social measures to be taken were all due to uncertainty. However, what should be the necessary actions to take in such deeply uncertain situation where there is no or very little...

Optimal Adaptive Policymaking under Deep Uncertainty? Yes we can!

Uncertainty manifests itself in almost every aspect of decision making. Adaptive and flexible policy design becomes crucial under uncertainty. An adaptive policy is designed to be flexible and can be adapted over time to changing circumstances and unforeseeable surprises. A crucial part of an adaptive policy is the monitoring system and...