Top

previous chapter Constraint-Based Local Search

next chapter Theory of Local Search

Hint

Swipe to navigate through the chapters of this book

2018 | OriginalPaper | Chapter

10. Guided Local Search

Read first chapter

Authors: Abdullah Alsheddy, Christos Voudouris, Edward P. K. Tsang, Ahmad Alhindi

Publisher: Springer International Publishing

Published in: Handbook of Heuristics

» Get access to the full-text

Abstract

Guided local search (GLS) is a meta-heuristic method proposed to solve combinatorial optimization problems. It is a high-level strategy that applies an efficient penalty-based approach to interact with the local improvement procedure. This interaction creates a process capable of escaping from local optima, which improves the efficiency and robustness of the underlying local search algorithms. Fast local search (FLS) is a way of reducing the size of the neighborhood to improve the efficiency of local search. GLS can be efficiently combined with FLS in the form of guided fast local search (GFLS). This chapter describes the principles of GLS and provides guidance for implementing and using GLS, FLS, and GFLS. It also surveys GLS extensions, hybrids, and applications to optimization, including multi-objective optimization.

Please log in to get access to this content

To get access to this content you need the following product:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 69.000 Bücher
über 500 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Umwelt
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Testen Sie jetzt 30 Tage kostenlos.

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 50.000 Bücher
über 380 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Umwelt
Maschinenbau + Werkstoffe

Testen Sie jetzt 30 Tage kostenlos.

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 58.000 Bücher
über 300 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Testen Sie jetzt 30 Tage kostenlos.

inform now

Aardal K, Van Hoesel S, Koster A, Mannino C, Sassano A (2007) Models and solution techniques for frequency assignment problems. Ann Oper Res 153(1):79–129

Alhindi A (2015) Multiobjective evolutionary algorithm based on decomposition with advanced local search methods. PhD thesis, Department of computer science, University of Essex, Colchester

Alhindi A, Zhang Q (2013) MOEA/D with guided local search: some preliminarily experimental results. In: 5th computer science and electronic engineering conference (CEEC), Colchester, pp 109–114

Alsheddy A (2011) Empowerment scheduling: a multi-objective optimization approach using guided local search. PhD thesis, Department of computer science, University of Essex, Colchester

Alsheddy A, Tsang EPK (2009) Guided pareto local search and its application to the 0/1 multi-objective knapsack problems. In: Metaheuristics international conference (MIC2009), Hamburg

Alsheddy A, Tsang EPk (2010) Guided pareto local search based frameworks for biobjective optimization. In: IEEE congress on evolutionary computation (CEC), Barcelona, pp 1–8

Alsheddy A, Tsang EPk (2011) Empowerment scheduling for a field workforce. J Sched 14(6):639–654

Anderson CA, Fraughnaugh K, Parker M, Ryan J (1993) Path assignment for call routing: an application of tabu search. Ann Oper Res 41:301–312

Azarmi N, Abdul-Hameed W (1995) Workforce scheduling with constraint logic programming. BT Technol J 13(1):81–94

10.

Backer BD, Furnon V, Shaw P, Kilby P and Prosser P (2000) Solving vehicle routing problems using constraint programming and metaheuristics. J Heuristics 6(4):501–523

11.

Basharu M, Arana I, Ahriz H (2005) Distributed guided local search for solving binary DisCSPs. In: Proceedings of FLAIRS 2005. AAAI Press, Clearwater Beach, pp 660–665

12.

Bentley JJ (1992) Fast algorithms for geometric traveling salesman problems. ORSA J Comput 4:387–411

13.

Beullens P, Muyldermans L, Cattrysse D, Van Oudheusden D (2003) A guided local search heuristic for the capacitated arc routing problem. Eur J Oper Res 147(3):629–643

14.

Bouju A, Boyce JF, Dimitropoulos CHD, vom Scheidt G, Taylor JG (1995) Intelligent search for the radio link frequency assignment problem. In: Proceedings of the international conference on digital signal processing, Limassol

15.

Castillo-Salazar A, Landa-Silva D, Qu R (2016) Workforce scheduling and routing problems: literature survey and computational study. Ann Oper Res 239(1):39–67

16.

Chiarandini M, Stutzle T (2007) Stochastic local search algorithms for graph set T-colouring and frequency assignment. Constraints 12(3):371–403

17.

Chu P, Beasley JE (1997) A genetic algorithm for the generalized assignment problem. Comput Oper Res 24:17–23

18.

Congram RK, Potts CN (1999) Dynasearch algorithms for the traveling salesman problem. In: Presentation at the travelling salesman workshop, CORMSIS, University of Southampton, Southampton

19.

Cramer S, Kampouridis M (2015) Optimising the deployment of fibre optics using guided local search. In: Proceedings of the 2015 IEEE congress on evolutionary computation (CEC). IEEE Press, Sendai, pp 799–806

20.

Croes A (1958) A method for solving traveling-salesman problems. Oper Res 5:791–812

21.

Daoud S, Chehade H, Yalaoui F, Amodeo L (2014) Solving a robotic assembly line balancing problem using efficient hybrid methods. J Heuristics 20(3):235–259

22.

Daum M, Menzel W (2002) Parsing natural language using guided local search. In: Proceedings of 15th European conference on artificial intelligence (ECAI-2002), Lyon, pp 435–439

23.

Davenport A, Tsang EPK, Wang CJ, Zhu K (1994) GENET: a connectionist architecture for solving constraint satisfaction problems by iterative improvement. In: Proceedings of 12th national conference for artificial intelligence (AAAI), Seattle, 325–330

24.

Dorne R, Voudouris C, Liret A, Ladde C, Lesaint D (2003) iSchedule – an optimisation tool-kit based on heuristic search to solve BT scheduling problems. BT Technol J 21(4):50–58

25.

Dorne R, Mills P, Voudouris C (2007) Solving vehicle routing using iOpt. In: Doerner KF et al (eds) Metaheuristics: progress in complex systems optimization. Operations research/computer science interfaces series, vol 39. Springer, New York, pp 389–408

26.

Egeblad J, Nielsen B, Odgaard A (2007) Fast neighbourhood search for two- and three-dimensional nesting problems. Eur J Oper Res 183(3):1249–1266

27.

Faroe O, Pisinger D, Zachariasen M (2003) Guided local search for final placement in VLSI design. J Heuristics 9:269–295

28.

Flood MM (1956) The traveling-salesman problem. In: Operations research, vol 4. Columbia University, New York, pp 61–75

29.

Flores Lucio G, Reed M, Henning I (2007) Guided local search as a network planning algorithm that incorporates uncertain traffic demands. Comput Netw 51(11):3172–3196

30.

Freisleben B, Merz P (1996) A genetic local search algorithm for solving symmetric and asymmetric travelling salesman problems. In: Proceedings of the 1996 IEEE international conference on evolutionary computation. IEEE Press, Piscataway, pp 616–621

31.

Gent IP, van Maaren H, Walsh T (2000) SAT2000, highlights of satisfiability research in the year 2000. Frontiers in artificial intelligence and applications. IOS Press, Amsterdam/Washington, DC

32.

Glover F, Laguna M (1997) Tabu search. Kluwer Academic, Boston

33.

GLS Demos (2008). http://cswww.essex.ac.uk/CSP/glsdemo.html

34.

Gomes N, Vale Z, Ramos C (2003) Hybrid constraint algorithm for the maintenance scheduling of electric power units. In: Proceeding Of international conference on intelligent systems application to power systems (ISAP 2003), Lemnos

35.

Hani Y, Amodeo L, Yalaoui F, Chen H (2007) Ant colony optimization for solving an industrial layout problem. Eur J Oper Res 183(2):633–642

36.

Hansen P, Mladenović N, Todosijević R (2016) Variable neighborhood search: basics and variants. EURO J Comput Optim 1–32

37.

Hifi M, Michrafy M, Sbihi A (2004) Heuristic algorithms for the multiple-choice multidimensional Knapsack problem. J Oper Res Soc 55:1323–1332

38.

Holstein D, Moscato P (1999) Memetic algorithms using guided local search: a case study. In: Corne D, Glover F, Dorigo M (eds) New ideas in optimisation. McGraw-Hill, London, pp 235–244

39.

Johnson D (1990) Local optimization and the traveling salesman problem. In: Proceedings of the 17th colloquium on automata languages and programming. Lecture notes in computer science, vol 443. Springer, London, pp 446–461

40.

Kilby P, Prosser P, Shaw P (1999) Guided local search for the vehicle routing problem with time windows. In: Voss S, Martello S, Osman IH, Roucairol C (eds) Meta-heuristics: advances and trends in local search paradigms for optimization. Kluwer Academic, Boston, pp 473–486

41.

Knox J (1994) Tabu search performance on the symmetric traveling salesman problem. Comput Oper Res 21(8):867–876

42.

Koopman BO (1957) The theory of search, part III, the optimum distribution of search effort. Oper Res 5:613–626

43.

Kytöjoki J, Nuortio T, Bräysy O, Gendreau M (2007) An efficient variable neighbourhood search heuristic for very large scale vehicle routing problems. Comput Oper Res 34(9): 2743–2757

44.

Langer Y, Bay M, Crama Y, Bair F, Caprace JD, Rigo P (2005) Optimization of surface utilization using heuristic approaches. In: Proceedings of the international conference COMPIT’05, Hamburg, pp 419–425

45.

Lau TL (1999) Guided genetic algorithm. PhD thesis, Department of computer science, University of Essex, Colchester

46.

Lau TL, Tsang EPK (1998) Guided genetic algorithm and its application to the radio link frequency allocation problem. In: Proceedings of NATO symposium on frequency assignment, sharing and conservation in systems (AEROSPACE), Aalborg, AGARD, RTO-MP-13, paper No.14b

47.

Lau TL, Tsang EPK (1998) The guided genetic algorithm and its application to the general assignment problem. In: IEEE 10th international conference on tools with artificial intelligence (ICTAI’98), Taiwan, pp 336–343

48.

Lin S (1965) Computer solutions of the traveling-salesman problem. Bell Syst Tech J 44: 2245–2269

49.

Lin S, Kernighan BW (1973) An effective heuristic algorithm for the traveling salesman problem. Oper Res 21:498–516

50.

Martin O, Otto SW (1966) Combining simulated annealing with local search heuristics. Ann Operat Res 63(1):57–75

51.

Mester D, Bräysy O (2005) Active guided evolution strategies for large-scale vehicle routing problems with time windows. Comput Oper Res 32(6):1593–1614

52.

Mester DI, Ronin YI, Nevo E, Korol AB (2004) Fast and high precision algorithms for optimization in large-scale genomic problems. Comput Biol Chem 28(4):281–290

53.

Mills P, Tsang EPK (2000) Guided local search for solving SAT and weighted MAX-SAT problems. J Autom Reason 24:205–223

54.

Mills P, Tsang E, Ford J (2003) Applying an extended guided local search to the quadratic assignment problem. Ann Ope Res 118:1–4/121–135

55.

Moghrabi I (2006) Guided local search for query reformulation using weight propagation. Int J Appl Math Comput Sci (AMCS) 16(4):537–549

56.

Murphey RA, Pardalos PM, Resende MGC (1999) Frequency assignment problems. In: Du D-Z, Pardalos P (eds) Handbook of combinatorial optimization. vol 4, Kluwer Academic, Boston

57.

Padron V, Balaguer C (2000) New methodology to solve the RPP by means of isolated edge. In: Tuson A (ed) Cambridge conference tutorial papers. Young OR, vol 11. Operational Research Society, UK

58.

Paquete L, Chiarandini M, Stützle T (2004) Pareto local optimum sets in the biobjective traveling salesman problem: an experimental study. In: Gandibleux X (ed) Metaheuristics for multiobjective optimisation, vol 535. Springer, Berlin/New York, pp 177–199

59.

Peh S, Hong J (2016) GLSDock – drug design using guided local search. In: Proceedings of the 2016 international conference on computational science and its applications, Beijing, pp 11–21

60.

Pesant G, Gendreau M (1999) A constraint programming framework for local search methods. J Heuristics 5(3)255–279

61.

Rahman MK, Nayeem MA, Rahman MS (2015) Transit network design by hybrid guided genetic algorithm with elitism. In: Proceedings of the 2015 conference on advanced systems for public transport (CASPT), Rotterdam

62.

Reinelt G (1991) A traveling salesman problem library. ORSA J Comput 3:376–384

63.

Resende MGC, Feo TA (1996) A GRASP for satisfiability. In: Johnson DS, Trick MA (eds) Cliques, coloring, and satisfiability: second DIMACS implementation challenge. DIMACS series on discrete mathematics and theoretical computer science, vol 26. American Mathematical Society, Providence, pp 499–520

64.

Selman B, Kautz H (1993) Domain-independent extensions to GSAT: solving large structured satisfiability problems. In: Proceeding of 13th international joint conference on AI, Chambéry, pp 290–295

65.

Selman B, Levesque HJ, Mitchell DG (1992) A new method for solving hard satisfiability problems. In: Proceedings of AAAI-92, San Jose, pp 40–446

66.

Shaghaghi A, Glover T, Kampouridis M, Tsang E (2013) Guided local search for optimal GPON/FTTP network design. In: Chaki N et al (eds) Computer networks & communications (NetCom): proceedings of the fourth international conference on networks & communications. Springer, New York, pp 255–263

67.

Shang Y, Wah BW (1998) A discrete Lagrangian-based global-search method for solving satisfiability problems. J Glob Optim 12(1):61–99

68.

Simon HU (1989) Approximation algorithms for channel assignment in cellular radio networks. In: Proceedings 7th international symposium on fundamentals of computation theory. Lecture notes in computer science, vol 380. Springer, Berlin/New York, pp 405–416

69.

Stone LD (1983) The process of search planning: current approaches and continuing problems. Oper Res 31:207–233

70.

Tairan N, Algarni A, Varghese J, Jan M (2015) Population-based guided local search for multidimensional knapsack problem. In: Proceedings of the 2015 fourth international conference on future generation communication technology (FGCT), Luton, pp 1–5

71.

Tairan N, Zhang Q (2013) P-GLS-II: an enhanced version of the population-based guided local search. In: Proceedings of the 13th annual conference on genetic and evolutionary computation (GECCO), Dublin, pp 537–544

72.

Tamura H, Zhang Z, Tang Z, Ishii M (2006) Objective function adjustment algorithm for combinatorial optimization problems. IEICE Trans Fundam Electron Commun Comput Sci E89-A:9:2441–2444

73.

Tarantilis CD, Zachariadis EE, Kiranoudis CT (2008) A guided tabu search for the heterogeneous vehicle routeing problem. J Oper Res Soc 59(12):1659–1673

74.

Tarantilis CD, Zachariadis EE, Kiranoudis CT (2008) A hybrid guided local search for the vehicle-routing problem with intermediate replenishment facilities. INFORMS J Comput 20(1)154–168

75.

Tikhonov AN, Arsenin VY (1977) Solutions of ill-posed problems. Wiley, New York

76.

Tsang EPK, Voudouris C (1997) Fast local search and guided local search and their application to British Telecom’s workforce scheduling problem. Oper Res Lett 20(3):119–127

77.

Tsang EPK, Wang CJ, Davenport A, Voudouris C, Lau TL (1999) A family of stochastic methods for constraint satisfaction and optimisation. In: Proceedings of the first international conference on the practical application of constraint technologies and logic programming (PACLP), London, pp 359–383

78.

Vansteenwegen P, Souffriau W, Berghe G, Oudheusden D (2009) A guided local search metaheuristic for the team orienteering problem. Eur J Oper Res 196(1):118–127

79.

Voudouris C (1997) Guided local search for combinatorial optimisation problems. PhD thesis, Department of computer science, University of Essex, Colchester

80.

Voudouris C, Tsang EPK (1996) Partial constraint satisfaction problems and guided local search. In: Proceedings of PACT’96, London, pp 337–356

81.

Voudouris C, Tsang E (1998) Solving the radio link frequency assignment problems using guided local search. In: Proceedings of NATO symposium on frequency assignment, sharing and conservation in systems (AEROSPACE), Aalborg, AGARD, RTO-MP-13, paper No. 14a

82.

Voudouris C, Tsang EPK (1999) Guided local search and its application to the travelling salesman problem. Eur J Oper Res 113(2):469–499

83.

Voudouris C, Dorne R, Lesaint D, Liret A (2001) iOpt: a software toolkit for heuristic search methods. In: Walsh T (ed) Practice of constraint programming – CP 2001, Paphos. Lecture notes in computer science, vol 2239, pp 716–729

84.

Xiaohu T, Haubrich H-J (2005) A hybrid metaheuristic method for the planning of medium-voltage distribution networks. In: Proceedings of 15th power systems computation conference (PSCC 2005), Liege

85.

Zachariadis E, Tarantilis C, Kiranoudis C (2009) A guided tabu search for the vehicle routing problem with two-dimensional loading constraints. Eur J Oper Res 195(3):729–743

86.

Zachariadis E, Tarantilis C, Kiranoudis C (2009) A hybrid metaheuristic algorithm for the vehicle routing problem with simultaneous delivery and pick-up service. Expert Syst Appl 36(2):1070–1081

87.

Zhang Q, Hui L (2007) MOEA/D: a multiobjective evolutionary algorithm based on decomposition. IEEE Trans Evol Comput 11:712–731

88.

Zhang Q, Sun J, Tsang EPK, Ford J (2003) Combination of guided local search and estimation of distribution algorithm for solving quadratic assignment problem. In: Bird of a feather workshops, genetic and evolutionary computation conference, Chicago

89.

Zhong Y, Cole MH (2005) A vehicle routing problem with backhauls and time windows: a guided local search solution. Transp Res E Logist Transp Rev 41(2):131–144 CrossRef

Title

Guided Local Search

Book

Handbook of Heuristics

Print ISBN: 978-3-319-07123-7

Electronic ISBN: 978-3-319-07124-4

https://doi.org/10.1007/978-3-319-07124-4

DOI

https://doi.org/10.1007/978-3-319-07124-4_2

Authors:

Abdullah Alsheddy
Christos Voudouris
Edward P. K. Tsang
Ahmad Alhindi

Publisher

Springer International Publishing

Sequence number

Chapter number

Premium Partner

Image Credits