Candidate List and Exploration Strategies for Solving 0/1 Mip Problems Using a Pivot Neighborhood

Candidate list strategies play an important role in designing efficient local search heuristics for combinatorial optimization problems. We look at various neighborhood exploration and exploitation strategies for 0/1 MIP problems using a pivoting neighborhood and simple tabu search. This neighborhood is quite costly to evaluate, particularly for large problems. Special attention is also given to the tableau based neighborhood structure. General guidelines based on computational experience are reported.