In this paper, we discuss analog neural approaches to the quadratic assignment problem (QAP). These approaches employ a hard constraints scheme to restrict ...

Recommendations · An algorithm for the generalized quadratic assignment problem · A New Semidefinite Programming Relaxation for the Quadratic Assignment Problem ...

In this paper, we propose new analog neural approaches to combinatorial optimization prob- lems. In particular, we deal with quadratic assignment problems (QAPs) ...

Oct 2, 2023 · We propose a method to solve the original Koopmans-Beckman formulation of the QAP using deep reinforcement learning. Our approach relies on a ...

Oct 22, 2024 · Many optimization models of neural networks need constraints to restrict the space of outputs to a subspace which satisfies external criteria.

Sep 1, 2000 · In this article, we propose new analog neural approaches to combinatorial optimization problems, in particular, quadratic assignment ...

May 7, 2021 · This paper presents a QAP network directly learning with the affinity matrix (equivalently the association graph) whereby the matching problem is translated ...

This chapter introduces quadratic assignment problems (QAP) as models for finding an optimal assignment among two sets of interrelated objects.

May 21, 2024 · We propose new analog neural approaches to quadratic assignment problems. Our methods are based on an analog version of the λ-opt heuristics ...

Oct 22, 2024 · Many combinatorial optimization problems can be described using the IQP formulation, such as the quadratic assignment problem (Anstreicher 2003) ...