Backbone guided tabu search for solving the UBQP problem

Wang, Yan; Lu, Zhengding; Glover, Fred; Hao, Jin‐Kao

doi:10.1007/s10732-011-9164-4

Cited by 31 publications

(28 citation statements)

References 29 publications

(32 reference statements)

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“…Specifically, it exploits critical variables identified as strongly determined, and has come to be one of the basic strategies associated with tabu search. This idea has also been used in our recent work [34]. Let x = {x 1 , x 2 , ..., x n }, indexed by N = {1, .…”

Section: Solution Reconstructionmentioning

confidence: 99%

Probabilistic GRASP-Tabu Search algorithms for the UBQP problem

Wang¹,

Lu²,

Glover³

et al. 2013

Computers & Operations Research

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This paper presents two algorithms combining GRASP and Tabu Search for solving the Unconstrained Binary Quadratic Programming (UBQP) problem. We first propose a simple GRASP-Tabu Search algorithm working with a single solution and then reinforce it by introducing a population management strategy. Both algorithms are based on a dedicated randomized greedy construction heuristic and a tabu search procedure. We show extensive computational results on two sets of 31 large random UBQP instances and one set of 54 structured instances derived from the MaxCut problem. Comparisons with state-of-the-art algorithms demonstrate the efficacy of our proposed algorithms in terms of both solution quality and computational efficiency. It is noteworthy that the reinforced GRASP-Tabu Search algorithm is able to improve the previous best known results for 19 MaxCut instances.

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Section: Solution Reconstructionmentioning

confidence: 99%

Probabilistic GRASP-Tabu Search algorithms for the UBQP problem

Wang¹,

Lu²,

Glover³

et al. 2013

Computers & Operations Research

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“…The tabu search procedure, that will be presented later in the paper, is known to be well-performing for solving singleobjective UBQP instances of different structures and sizes [12,13,14,15,16]. Of course, given that it manipulates a single solution only, a scalarization of the multiple objective functions is required due to the multiobjective nature of the mUBQP.…”

Section: Achievement Scalarizing Functionmentioning

confidence: 99%

“…During the past few decades, a large number of algorithms and approaches have been proposed for the single-objective UBQP in the literature. This includes several exact methods based on branch and bound or branch and cut [8,9,10] and a number of heuristic and metaheuristic methods like simulated annealing [11], tabu search [12,13,14,15,16], path-relinking [17], evolutionary and memetic algorithms [18,19,20,21].…”

Section: Introductionmentioning

confidence: 99%

A hybrid metaheuristic for multiobjective unconstrained binary quadratic programming

Liefooghe

Vérel

Hao

2014

Applied Soft Computing

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The conventional Unconstrained Binary Quadratic Programming (UBQP) problem is known to be a unified modeling and solution framework for many combinatorial optimization problems. This paper extends the single-objective UBQP to the multiobjective case (mUBQP) where multiple objectives are to be optimized simultaneously. We propose a hybrid metaheuristic which combines an elitist evolutionary multiobjective optimization algorithm and a state-of-the-art single-objective tabu search procedure by using an achievement scalarizing function. Finally, we define a formal model to generate mUBQP instances and validate the performance of the proposed approach in obtaining competitive results on large-size mUBQP instances with two and three objectives.

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“…Our recombination operator is inspired by the idea of backbone used in [2,22]. In the first step, the set of bids shared by the parents are identified and directly transfered to I 0 .…”

Section: Algorithm 1 the Recombination Operatormentioning

confidence: 99%

A Recombination-Based Tabu Search Algorithm for the Winner Determination Problem

Sghir¹,

Hao²,

Jaâfar³

et al. 2014

Lecture Notes in Computer Science

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Abstract. We propose a dedicated tabu search algorithm (TSX_WDP) for the winner determination problem (WDP) in combinatorial auctions. TSX_WDP integrates two complementary neighborhoods designed respectively for intensification and diversification. To escape deep local optima, TSX_WDP employs a backbone-based recombination operator to generate new starting points for tabu search and to displace the search into unexplored promising regions. The recombination operator operates on elite solutions previously found which are recorded in an global archive. The performance of our algorithm is assessed on a set of 500 well-known WDP benchmark instances. Comparisons with five state of the art algorithms demonstrate the effectiveness of our approach.

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Backbone guided tabu search for solving the UBQP problem

Cited by 31 publications

References 29 publications

Probabilistic GRASP-Tabu Search algorithms for the UBQP problem

Probabilistic GRASP-Tabu Search algorithms for the UBQP problem

A hybrid metaheuristic for multiobjective unconstrained binary quadratic programming

A Recombination-Based Tabu Search Algorithm for the Winner Determination Problem

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