Project : coprin
Keywords : local search, metaheuristics.
We have continued the development of the C++ INCOP library of incomplete methods for solving combinatorial optimization problems. This library offers classical local search methods such as simulated annealing, tabu search as well as a population based method, Go With the Winners. Several problems had been encoded, including Constraint Satisfaction Problems, graph coloring, frequency assignment.
We have this year extended the library into three directions :
A new simple local search metaheuristics named IDW (Intensification - Diversification Walk) has been developed. For selecting the next move, only a part of the neighborhood is explored and the first move leading to a better or equal configuration is chosen. When no such a move is found in that part of the neighborhood, the algorithm selects a worsening move. The main parameter of this algorithm is the size of the part of the neighborhood that is examined at each move (intensification) A second parameter defines two variants for escaping local minima when no better or equal neighbor has been found (diversification). IDW(any) chooses any worsening neighbor , and IDW (best) chooses the less worsening neighbor. This metaheuristics has given good results on different benchmarks (graph coloring, car sequencing, frequency assignment ...).
An automatic parameter tuning tool has been proposed : it can robustly tune the one or two parameters of simple local search algorithms such as simulated annealing, tabu search, IDW ,etc ...
New problems as the well known car sequencing problem defined in the CSP-LIB, and weighted n-ary CSPs defined in wcsp format proposed by de Givry(De Givry is a research scientist of INRA that tests exhaustively software for combinatorial optimization) can now be solved by INCOP.
The new version 1.1 of this library, named INCOP, is now available at http://www-sop.inria.fr/coprin/neveu/incop.