Characterizing and Analyzing the Relation Between Bin-Packing Problem and Tabu Search Algorithm

Abstract

The relation between problem and solution algorithm presents a similar phenomenon in different research problems (optimization, decision, classification, ordering); the algorithm performance is very good in some cases of the problem, and very bad in other. Majority of related works have worked for predicting the most adequate algorithm to solve a new problem instance. However, the relation between problem and algorithm is not understood at all. In this paper a formal characterization of this relation is proposed to facilitate the analysis and understanding of the phenomenon. Case studies for Tabu Search algorithm and One Dimension Bin Packing problem were performed, considering three important sections of algorithm logical structure. Significant variables of problem structure and algorithm searching behavior from past experiments, metrics known by scientific community were considered (Autocorrelation Coefficient and Length) and significant variables of algorithm operative behavior were proposed. The models discovered in the case studies gave guidelines that permits to redesign algorithm logical structure, which outperforms to the original algorithm in an average of 69%. The proposed characterization for the relation problem-algorithm could be a formal procedure for obtaining guidelines that improves the algorithm performance.