Improving last mile delivery, in terms of both efficiency and sustainability, has recently been
enhanced using truck/drone tandems. However, nearly all these approaches focus only on …

In the last decade, decision diagrams (DDs) have been the basis for a large array of novel
approaches for modeling and solving optimization problems. Many techniques now use DDs …

This tutorial provides an introduction to the use of decision diagrams for solving discrete
optimization problems. A decision diagram is a graphical representation of the solution …

Abstract Domain-independent dynamic programming (DIDP) is a recently proposed model-
based paradigm for combinatorial optimization where a problem is formulated as dynamic …

We present a message passing method for 0 {–} 1 integer linear programs. Our algorithm is
based on a decomposition of the original problem into subproblems that are represented as …

We present a massively parallel Lagrange decomposition method for solving 0--1 integer
linear programs occurring in structured prediction. We propose a new iterative update …

Dynamic programming (DP) is a framework used in multiple disciplines to solve decision-
making problems. In particular, in computer science and operations research (OR), DP …

Many discrete optimization problems are amenable to constrained shortest-path
reformulations in an extended network space, a technique that has been key in …

For vehicle routing problems, strong dual bounds on the optimal value are needed to
develop scalable exact algorithms as well as to evaluate the performance of heuristics. In …

Discrete optimization problems expressible as dynamic programs can be solved by branch-
and-bound with decision diagrams. This approach dynamically compiles bounded-width …