Influence of encoding and neighborhood in landscape analysis and tabu search performance for job shop scheduling problem

Abstract

Fitness landscape analysis is used to understand search spaces of combinatorial problems that can hardly be solved exactly, such as the job shop scheduling problem. We analyze the influence of the solution encodings and the neighborhood operators on usual metrics for landscape analysis, and try to correlate the results to the performance of a local search method such as tabu search using these encodings and operators for a wide range of instances of the job shop scheduling problem.