Combining heuristics and Exact Algorithms: A Review

TL;DR

This paper reviews the integration of heuristics and exact algorithms, highlighting recent hybrid approaches that leverage the strengths of both to solve complex optimization problems more effectively.

Contribution

It provides a comprehensive overview of hybrid methods combining mathematical programming and metaheuristics, emphasizing recent developments and potential benefits.

Findings

Hybrid methods improve solution quality for complex problems.

Combining heuristics and exact algorithms enhances computational efficiency.

Interdisciplinary collaboration accelerates innovation in optimization techniques.

Abstract

Several different ways exist for approaching hard optimization problems. Mathematical programming techniques, including (integer) linear programming-based methods and metaheuristic approaches, are two highly successful streams for combinatorial problems. These two have been established by different communities more or less in isolation from each other. Only over several years ago, a larger number of researchers recognized the advantages and huge potentials of building hybrids of mathematical programming methods and metaheuristics.