Experimental analysis of algorithms for the independent quadratic assignment problem

Abstract

The independent quadratic assignment problem is a variation of the well-known Koopmans–Beckman quadratic assignment problem. The model has a wide variety of applications but it is strongly NP-hard and is also hard to approximate. In this paper we present innovative and simple heuristic algorithms to optimize the problem based on the paradigms of local search, very large-scale neighborhood (VLSN) search, and local search with path-relinking. The performance of these algorithms are analyzed using results generated by extensive computational experiments. Our experimental study highlights that the strategies of path-relinking and VLSN search when worked in unison produced superior outcomes, outperforming algorithms that employ these strategies individually. This underscores the power of hybrid algorithmic approaches in solving complex optimization problems, in particular, the independent quadratic assignment problem. This is the first experimental study available on the independent quadratic assignment problem. We also have constructed (and made available) test instances with different characteristics which can be used as benchmarks in future experimental studies on the problem.