Improved Rank-One-Based Relaxations and Bound Tightening Techniques for the Pooling Problem

The pooling problem is a classical NP-hard problem in the chemical process and petroleum industries. This problem is modeled as a nonlinear, nonconvex network flow problem in which raw materials with different specifications are blended in some intermediate tanks, and mixed again to obtain the final products with desired specifications. The analysis of the pooling … Read more

Tightening Quadratic Convex Relaxations for the AC Optimal Transmission Switching Problem

The Alternating Current Optimal Transmission Switching (ACOTS) problem incorporates line switching decisions into the fundamental AC optimal power flow (ACOPF) problem. The advantages of the ACOTS problem are well-known in terms of reducing the operational cost and improving system reliability. ACOTS optimization models contain discrete variables and nonlinear, non-convex constraints, which make it difficult to … Read more

Presolving for Mixed-Integer Semidefinite Optimization

This paper provides a discussion and evaluation of presolving methods for mixed-integer semidefinite programs. We generalize methods from the mixed-integer linear case and introduce new methods that depend on the semidefinite condition. The considered methods include adding linear constraints, bounds relying on 2 × 2 minors of the semidefinite constraints, bound tightening based on solving … Read more

Three Enhancements for Optimization-Based Bound Tightening

Optimization-based bound tightening (OBBT) is one of the most effective procedures to reduce variable domains of nonconvex mixed-integer nonlinear programs (MINLPs). At the same time it is one of the most expensive bound tightening procedures, since it solves auxiliary linear programs (LPs)—up to twice the number of variables many. The main goal of this paper … Read more