Special Sessions

Abstract

Hexaly is a new kind of global optimization solver. Hexaly APIs unify modeling concepts from mixed-linear programming, nonlinear programming, and constraint programming. Its modeling interface is nonlinear and set-oriented. It also supports user-coded functions, thus enabling black-box optimization and, more particularly, simulation optimization. Under the hood, Hexaly combines various exact and heuristic optimization methods: spatial branch-and-bound, simplex methods, interior-point methods, automatic Dantzig-Wolfe reformulation, column and row generation, propagation methods, local search, population-based methods, and surrogate modeling techniques for black-box optimization. We illustrate these new modeling concepts on the seminal Traveling Salesman Problem (TSP), thus offering natural and compact modeling of the problem and performance on par with Concorde, the renowned TSP solver.

Constraint Programming - A Tutorial 

In this talk, I will provide a concise introduction to Constraint Programming (CP) technology. Given the limited time, I will focus on key aspects, including domain representation, state management and restoration during search, and the implementation of global constraints. I will briefly introduce notions of consistency and present the main global constraints commonly found in CP solvers. Additionally, I will discuss the fundamental principle behind most black-box search methods. Finally, I will show some CP models for well known optimization problems. This introduction is based on MiniCP: http://www.minicp.org.

Constraint Programming and Scheduling

Scheduling is one of the most successful problem classes for Constraint Programming (CP) with an increasing number of papers appearing in OR journals as well as in industrial applications. Over the past 20 years, CP researchers have exploited the extensibility of CP to develop scheduling specific variables types and constraints. In this talk, I will introduce interval variables and cumulative functions, demonstrate their use in modeling a single-machine inventory scheduling problem from EJOR 2020, and briefly touch on the underlying solution approaches.

Hybrid Optimization: Constraint Programming and Operations Research

This presentation discusses the integration of constraint programming with other optimization methods from operations research.  Three main streams are considered: 1) global constraint propagation based on combinatorial algorithms such as network flows, 2) optimization-based constraints that embed a linear or Lagrangian relaxation, and 3) decomposition methods including column generation and Benders decomposition.  For each of these we will discuss examples and references from the literature.

Abstract

This tutorial introduces participants to the practical application of Quantum Computing Inc's Dirac optimization devices through the eqc-models and qci-client open source software packages developed at QCi. We will explore the fundamentals of quantum computing as it pertains to optimization models, showcasing how Dirac devices can be leveraged to solve complex computational tasks. The session will cover the installation and configuration of the eqc-models package, provide hands-on demonstrations on programming and executing quantum optimization algorithms, and discuss real-world applications where these quantum technologies excel. Attendees will gain insights into the unique capabilities of Dirac devices, such as their use in machine learning, financial modeling, and logistics optimization, while learning to navigate the two interfaces.

Abstract

Updates on the INFORMS Journal on Computing and search for the new Editor-in-Chief.