Evolutionary approaches with adaptive operators for the bi-objective TTP

One characteristic feature of the traveling thief problem (TTP) is the existence of different facets of instance difficulty that make no single optimization algorithm to excel over the others. Multi-objective variants of the TTP add to the challenging features of the single-objective TTP the difficulties associated to keep a set of diverse non-dominated solutions. In this paper we propose an adaptive hybrid TTP optimization algorithm based on the probabilistic application of variation operators. The algorithm combines variation operators conceived for different facets of instance difficulty and adapts their frequency of application to the characteristics of the instances. The introduced algorithm shows a robust behavior across different bi-objective TTP instances producing results competitive with those achieved by state of the art algorithms.