Looking ahead with the pilot method

The pilot method as a meta-heuristic is a tempered greedy method aimed at obtaining better solutions while avoiding the greedy trap by looking ahead for each possible choice. Repeatedly a master solution is modified; each time in a minimal fashion to account for best choices, where choices are judged by means of a separate heuristic result, the pilot solution. The pilot method may be seen as a meta-heuristic enhancing the quality of (any) heuristic in a system for heuristic repetition. Experiments show that the pilot method as well as similar methods can behave quite competitively in comparison with well-known and accepted meta-heuristics. In this paper we review some less known results. As a higher time complexity is usually associated with repetition, we investigate a simple short-cut policy to reduce the running times, while retaining an enhanced solution quality. Furthermore, we report successful experiments that incorporate a distinguishing feature of the pilot method, which is the extension of neighborhoods into “local” search, creating tabu search hybrids.