Guided Local Search

Combinatorial explosion is a well-known phenomenon that prevents complete algorithms from solving many real-life combinatorial optimization problems. In many situations, heuristic search methods are needed. This chapter describes the principles of Guided Local Search (GLS) and Fast Local Search (FLS) and surveys their applications. GLS is a penalty-based metaheuristic algorithm that sits on top of other local search algorithms, with the aim to improve their efficiency and robustness. FLS is a way of reducing the size of the neighbourhood to improve the efficiency of local search. The chapter also provides guidance for implementing and using GLS and FLS. Four problems, representative of general application categories, are examined with detailed information provided on how to build a GLS-based method in each case.

[1]  M. M. Flood.  The Traveling-Salesman Problem , 1956 .

[2]  B. O. Koopman.  The Theory of Search , 1957 .

[3]  G. Croes.  A Method for Solving Traveling-Salesman Problems , 1958 .

[4]  Shen Lin.  Computer solutions of the traveling salesman problem , 1965 .

[5]  Brian W. Kernighan,et al.  An Effective Heuristic Algorithm for the Traveling-Salesman Problem , 1973, Oper. Res..

[6]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[7]  A. N. Tikhonov,et al.  Solutions of ill-posed problems , 1977 .

[8]  Lawrence D. Stone.  Feature Article - The Process of Search Planning: Current Approaches and Continuing Problems , 1983, Oper. Res..

[9]  R. Burkard.  Quadratic Assignment Problems , 1984 .

[10]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[11]  Cecilia R. Aragon,et al.  Optimization by Simulated Annealing: An Experimental Evaluation; Part I, Graph Partitioning , 1989, Oper. Res..

[12]  Hans Ulrich Simon,et al.  Approximation Algorithms for Channel Assignment in Cellular Radio Networks , 1989, FCT.

[13]  Fred Glover,et al.  Tabu Search - Part II , 1989, INFORMS J. Comput..

[14]  David S. Johnson,et al.  Local Optimization and the Traveling Salesman Problem , 1990, ICALP.

[15]  Jadranka Skorin-Kapov,et al.  Tabu Search Applied to the Quadratic Assignment Problem , 1990, INFORMS J. Comput..

[16]  Edward Tsang,et al.  Solving constraint satisfaction problems using neural networks , 1991 .

[17]  Gerhard Reinelt,et al.  TSPLIB - A Traveling Salesman Problem Library , 1991, INFORMS J. Comput..

[18]  Éric D. Taillard,et al.  Robust taboo search for the quadratic assignment problem , 1991, Parallel Comput..

[19]  Hector J. Levesque,et al.  A New Method for Solving Hard Satisfiability Problems , 1992, AAAI.

[20]  Edward Tsang,et al.  A Generic Neural Network Approach For Constraint Satisfaction Problems , 1992 .

[21]  Steven Minton,et al.  Minimizing Conflicts: A Heuristic Repair Method for Constraint Satisfaction and Scheduling Problems , 1992, Artif. Intell..

[22]  Sebastian Thrun,et al.  Efficient Exploration In Reinforcement Learning , 1992 .

[23]  Eugene C. Freuder,et al.  Partial Constraint Satisfaction , 1989, IJCAI.

[24]  Jon Jouis Bentley,et al.  Fast Algorithms for Geometric Traveling Salesman Problems , 1992, INFORMS J. Comput..

[25]  Mauricio G. C. Resende,et al.  A GRASP for satisfiability , 1993, Cliques, Coloring, and Satisfiability.

[26]  Fred W. Glover,et al.  A user's guide to tabu search , 1993, Ann. Oper. Res..

[27]  Jennifer Ryan,et al.  Path assignment for call routing: An application of tabu search , 1993, Ann. Oper. Res..

[28]  Bart Selman,et al.  Domain-Independent Extensions to GSAT : Solving Large StructuredSatis ability , 1993 .

[29]  Edward P. K. Tsang,et al.  Foundations of constraint satisfaction , 1993, Computation in cognitive science.

[30]  Panos M. Pardalos,et al.  The Quadratic Assignment Problem: A Survey and Recent Developments , 1993, Quadratic Assignment and Related Problems.

[31]  Andrew J. Davenport,et al.  GENET: A Connectionist Architecture for Solving Constraint Satisfaction Problems by Iterative Improvement , 1994, AAAI.

[32]  G. Reinelt.  The traveling salesman: computational solutions for TSP applications , 1994 .

[33]  Roberto Battiti,et al.  The Reactive Tabu Search , 1994, INFORMS J. Comput..

[34]  John Knox,et al.  Tabu search performance on the symmetric traveling salesman problem , 1994, Comput. Oper. Res..

[35]  É. Taillard.  COMPARISON OF ITERATIVE SEARCHES FOR THE QUADRATIC ASSIGNMENT PROBLEM. , 1995 .

[36]  Edward Tsang,et al.  A cascadable VLSI design for GENET , 1995 .

[37]  N. Azarmi,et al.  Workforce scheduling with constraint logic programming , 1995 .

[38]  Cor A. J. Hurkens,et al.  An overview of algorithmic approaches to frequency assignment problems , 1995 .

[39]  Jimmy Ho-Man Lee,et al.  A Framework for Integrating Artificial Neural Networks and Logic Programming , 1995, Int. J. Artif. Intell. Tools.

[40]  Olivier C. Martin,et al.  Combining simulated annealing with local search heuristics , 1993, Ann. Oper. Res..

[41]  Bernd Freisleben,et al.  A genetic local search algorithm for solving symmetric and asymmetric traveling salesman problems , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[42]  C. Voudouris,et al.  Partial Constraint Satisfaction Problems and Guided Local Search , 1996 .

[43]  John E. Beasley,et al.  A genetic algorithm for the generalised assignment problem , 1997, Comput. Oper. Res..

[44]  Patrick Prosser,et al.  Guided Local Search for the Vehicle Routing Problem , 1997 .

[45]  Nenad Mladenović,et al.  An Introduction to Variable Neighborhood Search , 1997 .

[46]  Edward P. K. Tsang,et al.  Solving the Processor Configuration Problems with a Mutation-Based Genetic Algorithm , 1997, Int. J. Artif. Intell. Tools.

[47]  Edward P. K. Tsang,et al.  Fast local search and guided local search and their application to British Telecom's workforce scheduling problem , 1997, Oper. Res. Lett..

[48]  Franz Rendl,et al.  QAPLIB – A Quadratic Assignment Problem Library , 1997, J. Glob. Optim..

[49]  Edward P. K. Tsang,et al.  The guided genetic algorithm and its application to the generalized assignment problem , 1998, Proceedings Tenth IEEE International Conference on Tools with Artificial Intelligence (Cat. No.98CH36294).

[50]  Peter J. Stuckey,et al.  Semantics for using Stochastic Constraint Solvers in Constraint Logic Programming , 1998, J. Funct. Log. Program..

[51]  Jin-Kao Hao,et al.  Tabu Search for Frequency Assignment in Mobile Radio Networks , 1998, J. Heuristics.

[52]  Benjamin W. Wah,et al.  A Discrete Lagrangian-Based Global-Search Method for Solving Satisfiability Problems , 1996, J. Glob. Optim..

[53]  C. Voudouris,et al.  Guided Local Search — an Illustrative Example in Function Optimisation , 1998 .

[54]  Michel Gendreau,et al.  A Constraint Programming Framework for Local Search Methods , 1999, J. Heuristics.

[55]  Edward P. K. Tsang,et al.  Guided local search and its application to the traveling salesman problem , 1999, Eur. J. Oper. Res..

[56]  Panos M. Pardalos,et al.  Frequency Assignment Problems , 1999, Handbook of Combinatorial Optimization.

[57]  Pablo Moscato,et al.  Memetic algorithms using guided local search: a case study , 1999 .

[58]  Hans van Maaren,et al.  Sat2000: Highlights of Satisfiability Research in the Year 2000 , 2000 .

[59]  Peter J. Stuckey,et al.  A Lagrangian reconstruction of GENET , 2000, Artif. Intell..

[60]  Patrick Prosser,et al.  Solving Vehicle Routing Problems Using Constraint Programming and Metaheuristics , 2000, J. Heuristics.

[61]  E. Tsang.  A Family of Stochastic Methods For Constraint Satisfaction and Optimisation , 2001 .

[62]  David Pisinger,et al.  Guided Local Search for Final Placement in VLSI Design , 2001, IEEE/ACM International Conference on Computer Aided Design. ICCAD 2001. IEEE/ACM Digest of Technical Papers (Cat. No.01CH37281).

[63]  Raphaël Dorne,et al.  iOpt: A Software Toolkit for Heuristic Search Methods , 2001, CP.

[64]  Wolfgang Menzel,et al.  Parsing Natural Language using Guided Local Search , 2002, ECAI.

[65]  David Lesaint,et al.  iSchedule — An Optimisation Tool-Kit Based on Heuristic Search to Solve BT Scheduling Problems , 2003 .

[66]  Edward P. K. Tsang,et al.  Applying an Extended Guided Local Search to the Quadratic Assignment Problem , 2003, Ann. Oper. Res..

[67]  David Pisinger,et al.  Guided Local Search for the Three-Dimensional Bin-Packing Problem , 2003, INFORMS J. Comput..

[68]  Luc Muyldermans,et al.  A guided local search heuristic for the capacitated arc routing problem , 2003, Eur. J. Oper. Res..

[69]  Mhand Hifi,et al.  Heuristic algorithms for the multiple-choice multidimensional knapsack problem , 2004, J. Oper. Res. Soc..

[70]  Thomas Stützle,et al.  Pareto Local Optimum Sets in the Biobjective Traveling Salesman Problem: An Experimental Study , 2004, Metaheuristics for Multiobjective Optimisation.

[71]  Eviatar Nevo,et al.  Fast and high precision algorithms for optimization in large-scale genomic problems , 2004, Comput. Biol. Chem..

[72]  Patrick Prosser,et al.  A Comparison of Traditional and Constraint-based Heuristic Methods on Vehicle Routing Problems with Side Constraints , 2000, Constraints.

[73]  Edward P. K. Tsang,et al.  Guided Local Search for Solving SAT and Weighted MAX-SAT Problems , 2000, Journal of Automated Reasoning.

[74]  Muhammed Basharu,et al.  Distributed Guided Local Search for Solving Binary DisCSPs , 2005, FLAIRS Conference.

[75]  Michael H. Cole,et al.  A VEHICLE ROUTING PROBLEM WITH BACKHAULS AND TIME WINDOWS: A GUIDED LOCAL SEARCH SOLUTION , 2005 .

[76]  Philippe Rigo,et al.  Optimization of Surface Utilization Using Heuristic Approaches , 2005 .

[77]  Olli Bräysy,et al.  Active guided evolution strategies for large-scale vehicle routing problems with time windows , 2005, Comput. Oper. Res..

[78]  Hiroki Tamura,et al.  Objective Function Adjustment Algorithm for Combinatorial Optimization Problems , 2006, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

[79]  Issam A. R. Moghrabi,et al.  GUIDED LOCAL SEARCH FOR QUERY REFORMULATION USING WEIGHT PROPAGATION , 2006 .

[80]  Jens Egeblad,et al.  Fast neighborhood search for two- and three-dimensional nesting problems , 2007, Eur. J. Oper. Res..

[81]  Carlo Mannino,et al.  Models and solution techniques for frequency assignment problems , 2003, 4OR.

[82]  Patrick Mills,et al.  Solving Vehicle Routing Using IOPT , 2007, Metaheuristics.

[83]  Qingfu Zhang,et al.  MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition , 2007, IEEE Transactions on Evolutionary Computation.

[84]  Ian D. Henning,et al.  Guided local search as a network planning algorithm that incorporates uncertain traffic demands , 2007, Comput. Networks.

[85]  Haoxun Chen,et al.  Ant colony optimization for solving an industrial layout problem , 2007, Eur. J. Oper. Res..

[86]  Thomas Stützle,et al.  Stochastic Local Search Algorithms for Graph Set T -colouring and Frequency Assignment , 2005 .

[87]  Michel Gendreau,et al.  An efficient variable neighborhood search heuristic for very large scale vehicle routing problems , 2007, Comput. Oper. Res..

[88]  Emmanouil E. Zachariadis,et al.  A guided tabu search for the heterogeneous vehicle routeing problem , 2008, J. Oper. Res. Soc..

[89]  Qingfu Zhang,et al.  Self-Guided Genetic Algorithm , 2008, ICIC.

[90]  Emmanouil E. Zachariadis,et al.  A Hybrid Guided Local Search for the Vehicle-Routing Problem with Intermediate Replenishment Facilities , 2008, INFORMS J. Comput..

[91]  Emmanouil E. Zachariadis,et al.  A hybrid metaheuristic algorithm for the vehicle routing problem with simultaneous delivery and pick-up service , 2009, Expert Syst. Appl..

[92]  Emmanouil E. Zachariadis,et al.  A Guided Tabu Search for the Vehicle Routing Problem with two-dimensional loading constraints , 2009, Eur. J. Oper. Res..

[93]  Dirk Van Oudheusden,et al.  A guided local search metaheuristic for the team orienteering problem , 2009, Eur. J. Oper. Res..

[94]  Edward P. K. Tsang,et al.  Guided Pareto Local Search based frameworks for biobjective optimization , 2010, IEEE Congress on Evolutionary Computation.

[95]  Abdullah Alsheddy,et al.  Empowerment Scheduling: A Multi-objective Optimization Approach Using Guided Local Search , 2011 .

[96]  Edward P. K. Tsang,et al.  Empowerment scheduling for a field workforce , 2011, J. Sched..

[97]  Qingfu Zhang,et al.  P-GLS-II: an enhanced version of the population-based guided local search , 2011, GECCO '11.