A Variable Depth Sequential Search Heuristic for the Quadratic Assignment Problem

TL;DR

This paper introduces a variable depth sequential search heuristic for the quadratic assignment problem, significantly enhancing solution quality when combined with tabu search, especially for larger instances.

Contribution

It presents a novel variable depth search heuristic inspired by TSP edge moves, improving solution performance for quadratic assignment problems.

Findings

Performance improved up to 15 times with heuristic plus tabu search.

Improvements grow larger as problem size increases.

Effective for unstructured instances of sizes 60 to 400.

Abstract

We develop a variable depth search heuristic for the quadratic assignment problem. The heuristic is based on sequential changes in assignments analogous to the Lin-Kernighan sequential edge moves for the traveling salesman problem. We treat unstructured problem instances of sizes 60 to 400. When the heuristic is used in conjunction with robust tabu search, we measure performance improvements of up to a factor of 15 compared to the use of robust tabu alone. The performance improvement increases as the problem size increases.