Optimal design of an electricity-intensive industrial facility subject to electricity price uncertainty: stochastic optimization and scenario reduction

When considering the design of electricity-intensive industrial processes, a challenge is that future electricity prices are highly uncertain. Design decisions made before construction can affect operations decades into the future. We thus explore whether including electricity price uncertainty into the design process affects design decisions. We apply stochastic optimization to the design and operations of … Read more

Branch-and-Cut-and-Price for Multi-Agent Pathfinding

There are currently two broad strategies for optimal Multi-agent Pathfinding (MAPF): (1) search-based methods, which model and solve MAPF directly, and (2) compilation-based solvers, which reduce MAPF to instances of well-known combinatorial problems, and thus, can benefit from advances in solver techniques. In this work, we present an optimal algorithm, BCP, that hybridizes both approaches … Read more

Planning for Dynamics under Uncertainty

Planning under uncertainty is a frequently encountered problem. Noisy observation is a typical situation that introduces uncertainty. Such a problem can be formulated as a Partially Observable Markov Decision Process (POMDP). However, solving a POMDP is nontrivial and can be computationally expensive in continuous state, action, observation and latent state space. Through this work, we … Read more

Chemotherapy operations planning and scheduling

Chemotherapy operations planning and scheduling in oncology clinics is a complex problem due to several factors such as the cyclic nature of chemotherapy treatment plans, the high variability in resource requirements (treatment time, nurse time, pharmacy time) and the multiple clinic resources involved. Treatment plans are made by oncologists for each patient according to existing … Read more

Dantzig-Wolfe and block coordinate-descent decomposition in large-scale integrated refinery-planning

The integrated refinery-planning (IRP), an instrumental problem in the petroleum industry, is made of several subsystems, each of them involving a large number of decisions. Despite the complexity of the overall planning problem, this work presents a mathematical model of the refinery operations char acterized by complete horizontal integration of subsystems from crude oil purchase … Read more

OR Counterparts to AI Planning

The term Planning is not used in Operations Research in the sense that is most common in Artificial Intelligence. AI Planning does have many features in common with OR scheduling, sequencing, routing, and assignment problems, however. Current approaches to solving such problems can be broadly classified into four areas: Combinatorial Optimization, Integer Programming, Constraint Programming, … Read more