Robustness Analysis for Adaptive Optimization With Application to Industrial Decarbonization in the Netherlands

Robustness analysis assesses the performance of a particular solution under variation in the input data. This is distinct from sensitivity analysis, which assesses how variation in the input data changes a model’s optimal solution. For risk assessment purposes, robustness analysis has more practical value than sensitivity analysis. This is because sensitivity analysis, when applied to … Read more

Efficient Project Scheduling with Autonomous Learning Opportunities

We consider novel project scheduling problems in which the experience gained from completing selected activities can be used to accelerate subsequent activities. Given a set of potential learning opportunities, our model aims to identify the opportunities that result in a maximum reduction of the project makespan when scheduled in sequence. Accounting for the impact of … Read more

Counterfactual Explanations for Linear Optimization

The concept of counterfactual explanations (CE) has emerged as one of the important concepts to understand the inner workings of complex AI systems. In this paper, we translate the idea of CEs to linear optimization and propose, motivate, and analyze three different types of CEs: strong, weak, and relative. While deriving strong and weak CEs … Read more

Relay-Hub Network Design for Consolidation Planning Under Demand Variability

Problem description: We study the problem of designing large-scale resilient relay logistics hub networks. We propose a model of Capacitated Relay Network Design under Stochastic Demand and Consolidation-Based Routing (CRND-SDCR), which aims to improve a network’s efficiency and resilience against commodity demand variability through integrating tactical decisions. Methodology: We formulate CRND-SDCR as a two-stage stochastic … Read more

The Service-Centric Vehicle Routing Problem with Crowdshipping

Last-mile delivery services worldwide have embraced crowdshipping, which involves both regular and occasional drivers to reduce transportation costs and potentially ensure timely deliveries. However, real-world uncertainty in travel times leads to delays in deliveries. Motivated by empirical studies on customer impatience with late deliveries, this paper focuses on a service-centric Vehicle Routing Problem with Crowdshipping … Read more

Freight consolidation through carrier collaboration – A cooperative game

Reducing inefficient truck movements, this research investigates the potential of freight consolidation through carrier collaboration. Considering the financial benefits of consolidation and the additional cost arising from collaboration, we propose a cooperative game to explore under which circumstances carriers can collaborate. We show that stable cost allocations are not always possible, affecting stability and thus … Read more

Optimal Sports League Realignment

We consider approaches for optimally organizing competitive sports leagues in light of competitive and logistical considerations. A common objective is to assign teams to divisions so that intradivisional travel is minimized. We present a bilinear programming formulation based on k-way equipartitioning, and show how this formulation can be extended to account for additional constraints and … Read more

Considering homeowner acceptance of retrofit measures within energy supply network optimization

A key factor towards a low-carbon society is energy efficient heating of private houses. The choice of heating technology as well as the decision for certain energy-efficient house renovations are made mainly by individual homeowners. In contrast, municipal energy network planning heavily depends on and strongly affects these decisions. Further, there are different conflicting objectives … Read more

Multistage Stochastic Facility Location under Facility Disruption Uncertainty

We consider a multistage variant of the classical stochastic capacitated facility location problem under facility disruption uncertainty. Two solution algorithms for this problem class are presented: (1) stochastic dual dynamic integer programming (SDDiP), the state-of-the-art algorithm for solving multistage stochastic integer programs, and (2) shadow price approximation (SPA), an algorithm utilizing trained parameters of the … Read more

Solving the three-dimensional open-dimension rectangular packing problem: a constraint programming model

In this paper, we address the three-dimensional open-dimension rectangular packing problem (3D-ODRPP). This problem addresses a set of rectangular boxes of given dimensions and a rectangular container of open dimensions. The objective is to pack all boxes orthogonally into the container while minimizing the container volume. Real-world applications of the 3D-ODRPP arise in production systems … Read more