Metaheuristics: A bibliography

Osman, Ibrahim H.; Laporte, Gilbert

doi:10.1007/bf02125421

Cited by 461 publications

(169 citation statements)

References 976 publications

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“…However, only small-sized instances can be solved exactly. To our knowledge, and according to Osman and Laporte [9], no one has ever applied metaheuristics to SPP resolution.…”

Section: The Set Packing Problemmentioning

confidence: 99%

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GRASP for set packing problems

Delorme

Gandibleux

Rodríguez³

2004

European Journal of Operational Research

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The principles of the Greedy Randomized Adaptative Search Procedure (GRASP) metaheuristic are instantiated for the set packing problem. We investigated several construction phases, and evaluated improvements based on advanced strategies. These improvements include a self-tuning procedure (using reactive GRASP), an intensification procedure (using path relinking) and a procedure involving the diversification of the selection (using a learning process). Two sets of various numerical instances were used to perform the computational experiments. The first set contains randomly generated instances, while the second includes instances relating to real problems in railway planning. No metaheuristic has previously been applied to this combinatorial problem. Consequently, we have discussed GRASPÕs performances both in relation to lower/upper bounds and to the results obtained with Cplex when such results are available. Our analysis, based on the average performances observed, shows the impact of the suggested strategies, and indicates the configuration that produces the best results.

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“…However, only small-sized instances can be solved exactly. To our knowledge, and according to Osman and Laporte [9], no one has ever applied metaheuristics to SPP resolution.…”

Section: The Set Packing Problemmentioning

confidence: 99%

“…• The values of items (c i ) are uniformly distributed in the interval [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] (weighted) or fixed to 1 (unicost).…”

Section: Randomly Generated Instancesmentioning

confidence: 99%

GRASP for set packing problems

Delorme

Gandibleux

Rodríguez³

2004

European Journal of Operational Research

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“…Both algorithms have been used to solve graphbased optimization problems [29] [30] with similar characteristics to the one presented here. These two alternative algorithmic approaches have been widely applied in several domains as it is discussed in [31].…”

Section: Experimental Comparisonmentioning

confidence: 99%

Learning semantically-annotated routes for context-aware recommendations on map navigation systems

Mocholi

Jaén

Krynicki

et al. 2012

Applied Soft Computing

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ElsevierMocholi Agües, JA.; Jaén Martínez, FJ.; Krynicki, KK.; Catalá Bolós, A.;Picón, A.;Cadenas, A. (2012) ABSTRACTModern technology has brought many changes to our everyday lives. Our need to be in constant touch with others has been met with the cellphone, which has become our companion and the convergence point of many technological advances. The combination of capabilities such as browsing the Internet and GPS reception has multiplied the services and applications based on the current location of the user.However, providing the user with these services has certain drawbacks. Although map navigation systems are the most meaningful way of displaying this information, the user still has to manually set up the filter in order to obtain a non-bloated visualization of the map and the available services. To tackle this problem, we present here a semantic multicriteria ant colony algorithm capable of learning the user's routes, including associated context information, and then predicting the most likely route a user is following, given his current location and context data. This knowledge could then be used as the basis for offering services related to his current (or most likely future) context data close to the path he is following. Our experimental results show that our algorithm is capable of obtaining consistent solutions sets even when multiple objective ontological terms are included in the process.

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“…Surveys and descriptions of applications can be found in van Laarhoven and Aarts [27], Osman and Laporte [23] or Aarts and Lenstra [1].…”

Section: Simulated Annealingmentioning

confidence: 99%

“…However, few practical applications appear in the literature. A short list can be found in the previous references, in particular in Osman and Laporte [23].…”

Section: Simulated Annealingmentioning

confidence: 99%

Simulated annealing for complex portfolio selection problems

Crama¹,

Schyns²

2003

European Journal of Operational Research

281

152

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This paper describes the application of a simulated annealing approach to the solution of a complex portfolio selection model. The model is a mixed integer quadratic programming problem which arises when Markowitz' classical mean-variance model is enriched with additional realistic constraints. Exact optimization algorithms run into di±culties in this framework and this motivates the investigation of heuristic techniques. Computational experiments indicate that the approach is promising for this class of problems.

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Metaheuristics: A bibliography

Cited by 461 publications

References 976 publications

GRASP for set packing problems

GRASP for set packing problems

Learning semantically-annotated routes for context-aware recommendations on map navigation systems

Simulated annealing for complex portfolio selection problems

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