H. R. Lourenco, O. Martin, and T. Stutzle. Iterated local search. In Glover and Kochenberger [17], pages 321--353.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....constructed an assignment, and before updating pheromone trails, we apply a local search procedure to improve the assignment constructed. Various local search procedures may be used to improve assignments (see, e.g. 16] for an experimental comparison of some of them) However, as pointed out in [18], when choosing the local search procedure to use in a metaheuristic, such as evolutionary algorithms, iterated local search or ACO, one has to nd a trade o between computation time and solution quality. In other words, one has to choose between a fast but not so good local search procedure or a ....

H.R. Lourenco, O. Martin, and T. Stutzle. Iterated local search. In F. Glover and G. Kochenberger, editors, Handbook of metaheuristics. Kluwer Academic Publishers, Dordrecht, The Netherlands, 2002, in press.

.... to be repaired by crossingover and or mutating complete assignments from the population; Guided Local Search [30] 31] escapes from local minima by increasing the weight of the violated constraints, in a e ort to ll up the local minimum until local search escapes it; Iterated Local Search [32] iteratively perturbates local minima before repairing them. Local search has proved to be e ective and ecient to solve very large CSPs, e.g. the million queens problem in [23] However, like complete search, local search often have more diculties in solving problems that are within the phase ....

....most promising states of the search space when constructing new assignments to be repaired. To solve a CSP with Ant Solver combined with local search, one has to provide the repair based local search procedure that must be used by ants to improved the constructed assignments. As pointed out in [32], when choosing the local search procedure used in a multi start type meta heuristic such as genetic algorithms, iterated local search or ACO, one has to nd a tradeo between computation time and solution quality. In other words, one has to choose between a fast but not so good local search ....

H.R. Lorenzo, O. Martin, and T. Stuetzle, \Iterated local search," in Handbook of metaheuristics, F. Glover and G. Kochenberger, Eds. 2001.

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H.R. Lourenco, O. Martin, and T. Stutzle. Iterated local search. In F. Glover and G. Kochenberger, editors, Handbook of Metaheuristics. Kluwer Academic Publishers, Boston, MA, USA, 2002. to appear. 11

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H. R. Lourenco, O. Martin, and T. Stutzle. Iterated local search. Technical Report AIDA-00-06, FG Intellektik, FB Informatik, TU Darmstadt, Germany, November 2000.

....known solutions. We therefore try to improve our local searches by means of some straightforward implementations of metaheuristics. Iterated Local Search Iterated local search (ILS) is a convenient way of iterating over a local search without incurring the known disadvantages of a random restart [31]. ILS does so by perturbing a locally optimal solution , leading to some intermediate solution , and then applying local search to , which finally leads to a (hopefully) new local optimum . An acceptance criterion then says whether or not we apply the next perturbation to or . An ....

H. R. Lourenco, O. Martin, and T. Stutzle. Iterated local search. In F. Glover and G. Kochenberger, editors, Handbook of Metaheuristics, volume 57, pages 321--353. Kluwer Academic Publishers, Norwell, MA, 2002.

.... is NP hard [15] In fact, exact algorithms can solve only small size instances [22] For larger instances approximate algorithms have to be used and a large number of such algorithms has been proposed [10, 14, 16, 17, 20] In this work we explore the application of Iterated Local Search (ILS) [21] to the GCP. ILS consists in the iterative application of a local search procedure to starting solutions that are obtained from the previous local optimum through a solution perturbation. The optimization variant of GCP can be stated as a sequence of constraint satisfaction problems, where k is ....

....condition met end Figure 1: Pseudocode of an iterated local search procedure (ILS) which is known to typically perform poorly. ILS is appealing both for its simplicity and for the very good results it provided, for example, in the Traveling Salesman Problem [18] or Scheduling Problems [21]. To apply an ILS algorithm, four components have to be specified. These are a procedure GenerateInitialSolution( that generates an initial solution s 0 , a procedure Perturbation, that modifies the current solution s leading to some intermediate solution s # , a procedure LocalSearch that ....

H.R. Lourenco, O. Martin, and T. Stutzle. Iterated local search. In F. Glover and G. Kochenberger, editors, Handbook of Metaheuristics. Kluwer Academic Publishers, Boston, MA, USA, 2002. to appear.

....attack the MPTTP. 3 Iterated Local Search (ILS) Iterated Local Search is a simple yet powerful SLS method, which is witnessed by excellent computational results for a variety of combinatorial optimisation problems like the travelling salesman problem (TSP) and several scheduling problems (see [17] for an overview) In a nutshell, ILS builds a biased random walk in the space of the local optima (with respect to some local search algorithm) This is done by iteratively perturbing a locally optimal solution, then applying a local search algorithm to obtain a new locally optimal solution, and ....

....The two single trajectory ILS algorithms only differ in the kind of perturbation they apply. In ILS # a number of insert moves is applied to the current candidate solution. This is done because good perturbations should somehow be complementary to the type of moves applied in the local search [17]. In particular, the perturbation allows to modify the number of jobs assigned to the processors, something which is not possible in the local search. The perturbation proceeds as follows: First, a processor is randomly chosen, second, a job ### # is randomly selected from the jobs on this ....

Lourenco, H.R., Martin, O., Stutzle, T.: Iterated local search. In Glover, F., Kochenberger, G., eds.: Handbook of Metaheuristics. Volume 57 of International Series in Operations Research & Management Science. Kluwer Academic Publishers, Norwell, MA (2002) 321--353

....directions for future work. 2 ILS for MAX SAT In this section we describe our Iterated Local Search (ILS) implementation for MAXSAT. ILS is a class of algorithms that essentially perform a biased random walk in the space of the local optima encountered by an underlying local search algorithm [14]. This walk is obtained by iteratively perturbing a locally optimal solution s # , then applying local search to obtain a new locally optimal solution s ## , and finally using an acceptance criterion to decide from which of the two solutions s # , s ## to continue the search. An algorithm outline ....

H. R. Lourenco, O. Martin, and T. St utzle. Iterated local search. In F. Glover and G. Kochenberger, editors, Handbook of Metaheuristics, volume 57 of International Series in Operations Research & Management Science, pages 321--353. Kluwer Academic Publishers, Norwell, MA, 2002.

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H. R. Lourenco, O. Martin, and T. Stutzle. Iterated local search. In Glover and Kochenberger [17], pages 321--353.

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H.R. Lourenco, O. Martin and T. Stutzle. (2003). Iterated local search. In: F. Glover and K. Kochenberher. (2003). Handbook of Meta-heuristics, Kluwer. Chapter 11, 321-354. Academic Publishers, Boston, MA, USA.

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Loureno, H.R., Martin, O.C. and Sttzle, T. (2003) Iterated Local Search. In Glover, F. and Kochenberger, G.A., editors, Handbook of Metaheuristics, pages 321-353. Kluwer Academic Publishers, Massachusetts, USA.

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H.R. Lourenco, O. Martin, and T. Stutzle. Iterated local search. In F. Glover and G. Kochenberger, editors, Handbook of Metaheuristics. Kluwer Academic Publishers, 2003.

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Lourenco, H., Martin, O., & Stutzle, T. (2003). Iterated local search. In Glover, F., & Kochenberger, G. (Eds.), Handbook of Metaheuristics. Kluwer Academic Publishers.

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H.R. Lourenco, O. Martin, and T. Stutzle. Iterated local search. In F. Glover and G. Kochenberger, editors, Handbook of metaheuristics. Kluwer Academic Publishers, Dordrecht, The Netherlands, 2002, in press.

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