Improving Iterated Local Search Solution for the Linear Ordering Problem with Cumulative Costs (LOPCC)

In this paper the linear ordering problem with cumulative costs is approached. The best known algorithm solution for the problem is the tabu search proposed by Duarte. In this work an experimental study was performed to evaluate the intensification and diversification balance between these phases. The results show that the heuristic construction phase has a major impact on the tabu search algorithm performance, which tends to diminish with large instances. Then to evaluate the diversification potential of the heuristic construction, two iterated local search algorithms were developed. Experimental evidence shows that the distribution of the heuristic construction proposed as diversification mechanism is more adequate for solving large instances. The diversification potential of the heuristic construction method was confirmed, because with this approach we found 26 best known solutions, not found by the tabu search algorithm.