An assumption-based combinatorial optimization system
H. Hara, Nobuhiro Yugami, H. Yoshida · 2003
An assumption-based combinatorial optimization system is proposed for solving combinatorial optimization problems. The assumption-based combinatorial optimization system is a local search method in which a solution is formulated as a set of assumptions. Minimal support for the objective function is a minimal set of assumptions that guarantee the value of the objective function. Using minimal support, the system finds an approximate optimal solution efficiently because it: reduces the number of neighbors, defends the loop of a search and prunes search space, and never stays at a local optimal solution. The system was applied to a jobshop scheduling problem, and the system's effectiveness compared with other methods was demonstrated.>