A High-Performance Parallel Algorithm for Multi-Objective Integer Optimization

TL;DR

This paper introduces PEA, an exact parallel algorithm for multi-objective integer optimization that leverages multicore hardware to efficiently solve larger problems with high scalability and theoretical soundness.

Contribution

The paper presents PEA, the first exact parallel algorithm that fully exploits multicore architectures for multi-objective integer optimization, improving scalability and problem size handling.

Findings

PEA can solve larger instances than previous algorithms.

PEA maintains the same number of scalarizations as sequential methods.

PEA is highly scalable and easy to implement.

Abstract

Multi-objective integer optimization problems are hard to solve, mainly because the number of nondominated images is often extremely large. We present the first exact algorithm, called PEA, that fully utilizes the multicore architecture of modern hardware. By exploiting the structure of the parameter set of the underlying scalarization, PEA can use a high number of threads while avoiding the usual pitfalls of parallel computing. It is highly scalable and easy to implement. As a result, PEA can solve much larger instances than previous state-of-the-art algorithms. Besides, PEA has a sound theoretical foundation. Unlike other existing parallel algorithms, it always solves the same number of scalarization problems as comparable sequential algorithms. We demonstrate the potential of PEA in a computational study.