Adaptive tabu search with strategic oscillation for the bipartite boolean quadratic programming problem with partitioned variables

Wang, Yan; Wu, Qinghua; Punnen, Abraham P.; Glover, Fred

doi:10.1016/j.ins.2018.03.045

Cited by 9 publications

(2 citation statements)

References 33 publications

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“…The solution improvement method (lines 14 and 25 in Algorithm 1) uses a 1-flip move based tabu search algorithm (Wang et al 2012(Wang et al , 2017(Wang et al , 2018, which performs the following iterations until the best solution cannot be improved for 5n consecutive iterations, called "the improvement cutoff ". Each iteration first identifies all 1-flip moves with respect to the current solution, each of which is obtained by changing the value of a single variable x i to its complementary value 1 − x i .…”

Section: The Solution Improvement Methodsmentioning

confidence: 99%

Clustering-driven evolutionary algorithms: an application of path relinking to the quadratic unconstrained binary optimization problem

Samorani

Wang

et al. 2019

J Heuristics

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A long-standing challenge in the metaheuristic literature is to devise a way to select parent solutions in evolutionary population-based algorithms to yield better offspring, and thus provide improved solutions to populate successive generations. We identify a way to achieve this goal that simultaneously improves the efficiency of the evolutionary process. Our strategy derives from a proposal associated with the scatter search and path relinking evolutionary algorithms that prescribes clustering the solutions and focusing on the two classes of solution combinations where the parents alternatively belong to the same cluster or to different clusters. We demonstrate the efficacy of our approach for selecting parents within this scheme by applying it to the important domain of quadratic unconstrained binary optimization (QUBO), which provides a model for solving a wide range of binary optimization problems. Within this setting, we focus on the path relinking algorithm, which together with tabu search has provided one of the most effective methods for QUBO problems. Computational tests disclose that our solution combination strategy improves the best results in the literature for hard QUBO instances.

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Section: The Solution Improvement Methodsmentioning

confidence: 99%

Clustering-driven evolutionary algorithms: an application of path relinking to the quadratic unconstrained binary optimization problem

Samorani

Wang

et al. 2019

J Heuristics

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“…Swap moves are employed to focus search attention to areas that do not feature in the tabu search list. A swap move is conducted if it will yield the highest move gain [34]. The variables cannot change their status once they have been included in the tabu list, but if the search leads to a potentially better solution, then a swap move is performed.…”

Section: Tabu Search (Ts)mentioning

confidence: 99%

Dynamic Street Parking Space Using Memetic Algorithm for Optimization

Akandwanaho¹,

Govender²

2020

Smart Urban Development

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In recent years, there have been an increasing number of automobiles in cities around the world. This is due to more people living and working in cities as a result of urbanization. Street parking remains a common option for motorists, due to it being cheap and convenient. However, this option leads to a high concentration of vehicles causing congestion and obstruction of traffic. This problem is compounded as motorists wait for others to pull out of parking bays or look for empty parking spaces. In order to provide relief to this problem, an intelligent approach is proposed that generates an optimal parking space based on the vehicle location and desired destination. The proposed approach applies its operators adaptively and it derives optimality from the synergy between genetic algorithm and a local search technique in the search optimization process. The proposed method exhibits superior performance when compared with the existing methods over multiple iterations.

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Dynamic Tabu Search for Enhancing the Productivity of a Bottle Production Line

Vié

Zufferey

2019

AIRO Springer Series

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Adaptive tabu search with strategic oscillation for the bipartite boolean quadratic programming problem with partitioned variables

Cited by 9 publications

References 33 publications

Clustering-driven evolutionary algorithms: an application of path relinking to the quadratic unconstrained binary optimization problem

Clustering-driven evolutionary algorithms: an application of path relinking to the quadratic unconstrained binary optimization problem

Dynamic Street Parking Space Using Memetic Algorithm for Optimization

Dynamic Tabu Search for Enhancing the Productivity of a Bottle Production Line

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