Abstract
The challenge of maximizing the diversity of a collection of points arises in a variety of settings, and the growing interest of dealing with diversity resulted in an effort to study the management of equity. While the terms diversity and dispersion can be found in many optimization problems indistinguishable, we undertake to explore the different models behind them.
In particular, this chapter describes the mathematical models for two diversity and three equity models. Additionally, we also review two related models that have recently received special attention. This chapter also reviews heuristics and metaheuristics for finding near-optimal solutions for these problems, where constructive and local search-based methods, such as greedy randomized adaptive search procedure (GRASP) and tabu search, play an important role.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
A\(\check {g}\)ca S, Eksioglu B, Ghosh JB (2000) Lagrangian solution of maximum dispersion problems. Nav Res Logist 47:97–114
Aringhieri R, Cordone R (2011) Comparing local search metaheuristics for the maximum diversity problem. J Oper Res Soc 62:266–280
Aringhieri R, Cordone R, Grosso A (2015) Construction and improvement algorithms for dispersion problems. Eur J Oper Res 242:21–33
Asada H, Toyama F, Shoji K, Miyamichi J (2010) Genetic local search with adaptative crossover probability and its application to maximum diversity problem. IEEJ Trans Electron Inf Syst 130:529–520
Brimberg J, Mladenovic N, Urosevic D, Ngai E (2009) Variable neighborhood search for the heaviest k-subgraph. Comput Oper Res 36:2885–2891
Campos V, Laguna M, Martí R (2005) Context-independient scatter and tabu search for permutation problems. INFORMS J Comput 17(1):111–122
Carrasco R, Pham A, Gallego M, Gortázar F, Martí R, Duarte A (2015) Tabu search for the max-mean dispersion problem, Knowledge based systems 85:256–264
Castillo O, Melin P, Gamez E, Kreinovich V, Kosheleva O (2009) Intelligence techniques are needed to further enhance the advantage with diversity in problem solving. In: IEEE workshop hybrid intelligent models and applications (HIMA’09), Nashville, pp 48–55
Dell’Amico M, Trubian M (1998) Solution of large weighted equicut problems. Eur J Oper Res 106:500–521
Della Groce F, Grosso A, Locatelli M (2009) A heuristic approach for the max-min diversity problem based on max-clique. Comput Oper Res 36(8):2429–2433
Deng Y, Bard JF (2011) A reactive GRASP with path relinking for capacitated clustering. J Heuristics 17:119–152
Duarte A, Martí R (2007) Tabu search and GRASP for the maximum diversity problem. Eur J Oper Res 178:71–84
Duarte A, Sánchez-Oro J, Resende M, Glover F, Martí R (2015) GRASP with exterior path relinking for differential dispersion minimization. Inf Sci 296(1):46–60
Erkut E (1990) The discrete p-dispersion problem. Eur J Oper Res 46:48–60
Erkut E, Neuman S (1989) Analytical models for locating undesirable facilities. Eur J Oper Res 40:275–291
Feo T, Goldschmidt O, Khellaf M (1992) One-half approximation algorithms for the k-partition problem. Oper Res 40:S170–S173
Freitas ARR, Guimarães FG, Pedrosa Silca RC, Souza MJF (2014) Memetic self-adaptive evolution strategies applied to the maximum diversity problem. Optim Lett 8(2): 705–714
French E (2005) The importance of strategic change in achieving equity in diversity. Strateg Change 14:35–44. Wiley InterScience
Gallego M, Laguna M, Martí R, Duarte A (2013) Tabu search with strategic oscillation for the maximally diverse grouping problem. J Oper Res Soc 64(5):724-734
Ghosh JB (1996) Computational aspects of the maximum diversity problem. Oper Res Lett 19:175–181
Glover F (1977) Heuristics for integer programming using surrogate constraints. Decis Sci 8(1):156–166
Glover F (2014) Exterior path relinking for zero-one optimization. Int J Appl Metaheuristic Comput 5(3):1–8
Glover F, Laguna M (1997) Tabu Search. Kluwer Academic Publishers, Boston
Glover F, Kuo CC, Dhir KS (1995) A discrete optimization model for preserving biological diversity. Appl Math Model 19:696–701
Glover F, Kuo CC, Dhir KS (1998) Heuristic algorithms for the maximum diversity problem. J Inf Optim Sci 19(1):109–132
Hansen P, Mladenovic N (2001) Variable neighborhood search: principles and aplications. Eur J Opns Res 130:449–467
Hansen P, Mladenovic N (2003) Variable neighborhood search. In: Glover F, Kochenberger G (eds) Handbook in metaheuristics. Kluwer Academic Publishers, Boston
Hassin R, Rubinstein S, Tamir A (1997) Approximation algorithms for maximum dispersion. Oper Res Lett 21:133–137
Katayama K, Narihisa H (2005) An evolutionary approach for the maximum diversity problem. In: Recent advances in memetic algorithms, vol 166. Springer, Berlin/New York, pp 31–47
Kincard RK (1992) Good solutions to discrete noxious location problems via metaheuristics. Ann Oper Res 40:265–281
Kuo CC, Glover F, Dhir KS (1993) Analyzing and modeling the maximum diversity problem by zero-one programming. Decis Sci 24:1171–1185
Laguna M, Marí R (2003) Scatter search: methodology and implementations in C. Kluwer Academic Publishers, Dordrecht
Martí R, Sandoya F (2013) GRASP and path relinking for the equitable dispersion problem. Comput Oper Res 40:3091–3099
Martínez-Gavara A, Campos V, Laguna M, Martí R (2016) Heuristic solution approaches for the maximum MinSum dispersion problem. J Glob Optim https://doi.org/10.1007/s10898-016-0429-1
Martínez-Gavara A, Campos V, Gallego M, Laguna M, Martí R (2015) Tabu Search and GRASP for the Capacited Clustering Problem. Comput Optim Appl 62:589–607
Mladenović N, Todosijević R, Urosević D (2016) Less is more: basic variable neighborhood search for minimum differential dispersion problem. Inf Sci 326:160171
Morán-Mirabal LF, González-Velarde JL, Resende MGC, Silva RMA (2013) Randomized heuristics for handover minimization in mobility networks. J Heuristics 19:845–880
O’Brien FA, Mingers J (1995) The equitable partitioning problem: a heuristic algorithm applied to the allocation of university student accommodation. Warwick Business School, Research Paper no. 187
Page SE (2007) The difference: how the power of diversity creates better groups, firms, schools, and societies. Princeton University Press, Princeton
Palubeckis G (2007) Iterated tabu search for the maximum diversity problem. Appl Math Comput 189(1):371–383
Pisinger D (2006) Upper bounds and exact algorithms for p-dispersion problems. Comput Oper Res 33:1380–1398
Porumbel D, Hao J, Glover F (2011) A simple and effective algorithm for the MaxMin diversity problem. Ann Oper Res 186(1):275–293
Prokopyev OA, Kong N, Martinez-Torres DL (2009) The equitable dispersion problem. Eur J Oper Res 197:59–67
Ravi SS, Rosenkrantz DJ, Tayi GK (1994) Heuristic and special case algorithms for dispersion problems. Oper Res 42:299–310
Resende MGC, Werneck R (2004) A hybrid heuristic for the p-median problem. J Heuristics 10(1):59–88
Resende MGC, Martí R, Gallego M, Duarte A (2010) GRASP and path relinking for the max−min diversity problem. Comput Oper Res 37(3):498–508
Wang J, Zhou Y, Cai Y, Yin J (2012) Learnable tabu search guided by estimation of distribution for maximum diversity problems. Soft Comput 16(4):711–728
Acknowledgements
This research has been partially supported by the Ministerio de Economía y Competitividad of Spain (Grant Refs. TIN2012-35632-C02 and TIN2015-65460-C2), the Generalitat Valenciana (ACOMP/2014/A/241 and Prometeo 2013/049), and the University of Valencia (UV-INV-PRECOMP13-115334).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this entry
Cite this entry
Sandoya, F., Martínez-Gavara, A., Aceves, R., Duarte, A., Martí, R. (2018). Diversity and Equity Models. In: Martí, R., Pardalos, P., Resende, M. (eds) Handbook of Heuristics. Springer, Cham. https://doi.org/10.1007/978-3-319-07124-4_61
Download citation
DOI: https://doi.org/10.1007/978-3-319-07124-4_61
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07123-7
Online ISBN: 978-3-319-07124-4
eBook Packages: Mathematics and StatisticsReference Module Computer Science and Engineering