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

Abstract

In this article we approach the linear ordering problem with cumulative costs (LOPCC). Bertacco developed this problem [2] and propose two exact algorithms, due to the complexity of the problem Duarte propose a Tabu algorithm for LOPCC [3] and until now that algorithm is the state of the art. In this ongoing research we propose a set of iterated local search algorithms (ILS) to solve the LOPCC. The experimental evidence shows that the performance of the iterated local search algorithms evaluated have similar quality to the best solution reported and get better efficiency than the reference solution. Also with the local search algorithms we improve the best known solution for 32 instances. Now we are working in developing new algorithms with population metaheuristics.