A Feasibility Pump Algorithm Embedded in an Annealing Framework

By Nicolas Pradignac, Maliheh Aramon, & Helmut G. Katzgraber
The feasibility pump algorithm is an efficient primal heuristic for finding feasible solutions to mixed-integer programming problems. The algorithm suffers mainly from fast convergence to local optima. In this paper, we investigate the effect of an alternative approach to circumvent this challenge by designing a two-stage approach that embeds the feasibility pump heuristic into an annealing framework. The algorithm dynamically breaks the discrete decision variables into two subsets based on the fractionality information obtained from prior runs, and enforces integrality on each subset separately. The feasibility pump algorithm iterates between rounding a fractional solution to one that is integral and projecting an infeasible integral solution onto the solution space of the relaxed mixed-integer programming problem. These two components are used in a Monte Carlo search framework to initially promote diversification and focus on intensification later. The computational results obtained from solving 91 mixed-binary problems demonstrate the superiority of our new approach over Feasibility Pump 2.0.

Most Recent Papers

Scaling Overhead of Locality Reduction in Binary Optimization Problems

By Elisabetta Valiante, Maritza Hernandez, Amin Barzegar, & Helmut G. Katzgraber Recently, there has been considerable interest in solving optimization problems by mapping these onto a binary representation, sparked mostly by the use of quantum annealing machines....

Quantum Multiple Kernel Learning

By Seyed Shakib Vedaie, Moslem Noori, Jaspreet S. Oberoi, Barry C. Sanders, & Ehsan Zahedinejad Kernel methods play an important role in machine learning applications due to their conceptual simplicity and superior performance on numerous machine learning tasks....

Variationally Scheduled Quantum Simulation

By Shunji Matsuura, Samantha Buck, Valentin Senicourt, & Arman Zaribafiyan Eigenstate preparation is ubiquitous in quantum computing, and a standard approach for generating the lowest-energy states of a given system is by employing adiabatic state preparation...