Abstract
Variable neighborhood search (VNS) is a well-known metaheuristic. Two main ingredients are needed for its design: a collection \(M=(N_1, \ldots , N_r)\) of neighborhood structures and a local search LS (often using its own single neighborhood L). M has a diversification purpose (search for unexplored zones of the solution space S), whereas LS plays an intensification role (focus on the most promising parts of S). Usually, the used set M of neighborhood structures relies on the same type of modification (e.g., change the value of i components of the decision variable vector, where i is a parameter) and they are built in a nested way (i.e., \(N_i\) is included in \(N_{i+1}\)). The more difficult it is to escape from the currently explored zone of S, the larger is i, and the more capability has the search process to visit regions of S which are distant (in terms of solution structure) from the incumbent solution. M is usually designed independently from L. In this paper, we depart from this classical VNS framework and discuss an extension, Collaborative Variable Neighborhood Search (CVNS), where the design of M and L is performed in a collaborative fashion (in contrast with nested and independent), and can rely on various and complementary types of modifications (in contrast with a common type with different amplitudes).
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References
Zufferey, N.: Metaheuristics: some principles for an efficient design. Comput. Technol. Appl. 3(6), 446–462 (2012)
Gendreau, M., Potvin, J.Y.: Handbook of Metaheuristics. International Series in Operations Research & Management Science, vol. 146. Springer, Heidelberg (2010). https://doi.org/10.1007/978-1-4419-1665-5
Mladenovic, N., Hansen, P.: Variable neighborhood search. Comput. Oper. Res. 24, 1097–1100 (1997)
Zufferey, N.: Optimization by ant algorithms: possible roles for an individual ant. Optim. Lett. 6(5), 963–973 (2012)
Thevenin, S., Zufferey, N.: Variable neighborhood search for a scheduling problem with time window penalties. In: Proceedings of the 14th International Workshop on Project Management and Scheduling (PMS 2014), Munich, Germany, April 2014
Bierlaire, M., Thémans, M., Zufferey, N.: A heuristic for nonlinear global optimization. INFORMS J. Comput. 22(1), 59–70 (2010)
Amrani, H., Martel, A., Zufferey, N., Makeeva, P.: A variable neighborhood search heuristic for the design of multicommodity production-distribution networks with alternative facility configurations. Oper. Res. Spectr. 33(4), 989–1007 (2011)
dos Santos, J.P.Q., de Melo, J.D., Neto, A.D.D., Aloise, D.: Reactive search strategies using reinforcement learning, local search algorithms and Variable Neighborhood Search. Expert Syst. Appl. 41, 4939–4949 (2014)
Li, K., Tian, H.: A two-level self-adaptive variable neighborhood search algorithm for the prize-collecting vehicle routing problem. Appl. Soft Comput. 43, 469–479 (2016)
Stenger, A., Vigo, D., Enz, S., Schwind, M.: An adaptive variable neighborhood search algorithm for a vehicle routing problem arising in small package shipping. Transp. Sci. 47(1), 64–80 (2013)
Mansouri, S.A., Gallear, D., Askariazad, M.H.: Decision support for build-to-order supply chain management through multiobjective optimization. Int. J. Prod. Econ. 135, 24–36 (2012)
Oguz, C., Salman, F.S., Yalcin, Z.B.: Order acceptance and scheduling decisions in make-to-order systems. Int. J. Prod. Econ. 125, 200–211 (2010)
Atan, M.O., Akturk, M.S.: Single CNC machine scheduling with controllable processing times and multiple due dates. Int. J. Prod. Res. 46, 6087–6111 (2008)
Shabtay, D., Gaspar, N., Yedidsion, L.: A bicriteria approach to scheduling a single machine with job rejection and positional penalties. J. Comb. Optim. 23, 395–424 (2013)
Thevenin, S., Zufferey, N., Widmer, M.: Tabu search for a single machine scheduling problem with discretely controllable release dates. In: 12th International Symposium on Operations Research in Slovenia (SOR 2013), pp. 1590–1595 (2013)
Liao, C.J., Cheng, C.C.: A variable neighborhood search for minimizing single machine weighted earliness and tardiness with common due date. Comput. Ind. Eng. 52, 404–413 (2007)
Hendel, Y., Sourd, F.: An improved earliness-tardiness timing algorithm. Comput. Oper. Res. 34, 2931–2938 (2007)
Bertsekas, D.P.: Nonlinear Programming, 2nd edn. Athena Scientific, Belmont (1999)
Bierlaire, M.: Introduction à l’optimisation différentiable. Presses Polytechniques et Universitaires Romandes, Lausanne, Switzerland (2013)
Conn, A.R., Gould, N.I.M., Toint, P.L.: Trust-Region Methods. Series on Optimization. MPS-SIAM, Philadelphia (2000)
Nocedal, J., Wright, S.J.: Numerical optimization. Operations Research. Springer, New York (1999). https://doi.org/10.1007/978-0-387-40065-5
Silver, E., Zufferey, N.: Inventory control of an item with a probabilistic replenishment lead time and a known supplier shutdown period. Int. J. Prod. Res. 49, 923–947 (2011)
Hedar, A., Fukushima, M.: Hybrid simulated annealing and direct search methods for nonlinear unconstrained global optimization. Optim. Methods Softw. 17, 891–912 (2002)
Chelouah, R., Siarry, P.: Genetic and nelder-mead algorithms hybridized for a more accurate global optimization of continuous multiminima functions. Eur. J. Oper. Res. 148, 335–348 (2003)
Hedar, A., Fukushima, M.: Heuristic pattern search and its hybridization with simulated annealing for nonlinear global optimization. Optim. Methods Softw. 19, 291–308 (2004)
Hedar, A., Fukushima, M.: Tabu search directed by direct search methods for nonlinear global optimization. Eur. J. Oper. Res. 170, 329–349 (2006)
Ahuja, R.K., Orlin, J.B., Pallattino, S., Scaparra, M.P., Scutella, M.G.: A multi-exchange heuristic for the single-source capacitated facility location problem. Manag. Sci. 50(6), 749–760 (2004)
Barahona, F., Chudak, F.A.: Near-optimal solutions to large-scale facility location problems. Discret. Optim. 2, 35–50 (2005)
Michel, L., Hentenryck, P.V.: A simple tabu search for warehouse location. Eur. J. Oper. Res. 157, 576–591 (2004)
Zhang, J., Chen, B., Ye, Y.: A multi-exchange local search algorithm for the capacitated facility location problem. Math. Oper. Res. 30(2), 389–403 (2005)
Hertz, A., Schindl, D., Zufferey, N.: Lower bounding and tabu search procedures for the frequency assignment problem with polarization constraints. 4OR 3(2), 139–161 (2005)
Ballou, R.H.: Business Logistics Management. Prentice Hall, Upper Saddle River (1992)
Schindl, D., Zufferey, N.: A learning tabu search for a truck allocation problem with linear and nonlinear cost components. Naval Res. Logist. 62(1), 32–45 (2015)
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Zufferey, N., Gallay, O. (2018). Collaborative Variable Neighborhood Search. In: Korošec, P., Melab, N., Talbi, EG. (eds) Bioinspired Optimization Methods and Their Applications. BIOMA 2018. Lecture Notes in Computer Science(), vol 10835. Springer, Cham. https://doi.org/10.1007/978-3-319-91641-5_27
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