Search Results - multi-objective unconstrained binary quadratic programming ((problem* OR problemy*) OR problems*)*

A multi-objective tabu search algorithm based on decomposition for multi-objective unconstrained binary quadratic programming problem

Authors: Ziyan Wu Keke Wu Jiahai Wang et al.

Source: Knowledge-Based Systems. 141:18-30

Subject Terms: 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://dblp.uni-trier.de/db/journals/kbs/kbs141.html#ZhouWWW18
https://www.sciencedirect.com/science/article/pii/S0950705117305300

A Decomposition-Based Multi-Objective Tabu Search Algorithm for Tri-Objective Unconstrained Binary Quadratic Programming Problem

Authors: Ying Zhou

Source: 22017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC). :101-107

Subject Terms: 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: http://ieeexplore.ieee.org/document/8005780/
https://dblp.uni-trier.de/db/conf/cse/cse2017-1.html#Zhou17
https://ieeexplore.ieee.org/document/8005780/

A directional-biased tabu search algorithm for multi-objective unconstrained binary quadratic programming problem

Authors: Jian Yin Jiahai Wang Ying Zhou

Source: 2013 Sixth International Conference on Advanced Computational Intelligence (ICACI). :281-286

Subject Terms: 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://ieeexplore.ieee.org/document/6748517/
http://ieeexplore.ieee.org/document/6748517/

Ensemble of multi-objective metaheuristic algorithms for multi-objective unconstrained binary quadratic programming problem

Authors: Ying Zhou Yiqiao Cai Lingjing Kong et al.

Source: Applied Soft Computing. 81:105485

Subject Terms: 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://dblp.uni-trier.de/db/journals/asc/asc81.html#ZhouKWLCL19
https://www.sciencedirect.com/science/article/pii/S1568494619302558
https://doi.org/10.1016/j.asoc.2019.105485

Solving bi-objective unconstrained binary quadratic programming problem with multi-objective path relinking algorithm

Authors: Lei Song Mingsheng Shang Yang Wang et al.

Source: 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD). :289-293

Subject Terms: 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Ensemble of multi-objective metaheuristic algorithms for multi-objective unconstrained binary quadratic programming problem.

Authors: Zhou, Ying Kong, Lingjing Wu, Ziyan et al.

Source: Applied Soft Computing. Aug2019, Vol. 81, p105485-105485. 1p.

Subject Terms: Metaheuristic algorithms, Quadratic programming, Combinatorial optimization, Mathematical optimization, NP-hard problems, Searching behavior

Solving Bi-objective Unconstrained Binary Quadratic Programming Problem with Multi-objective Backbone Guided Search Algorithm

Authors: Rong-Qiang Zeng Mingsheng Shang Li-Yuan Xue et al.

Source: Lecture Notes in Computer Science ISBN: 9783319422930

Access URL: https://rd.springer.com/chapter/10.1007/978-3-319-42294-7_66
https://dblp.uni-trier.de/db/conf/icic/icic2016-2.html#XueZWS16
https://doi.org/10.1007/978-3-319-42294-7_66
https://link.springer.com/chapter/10.1007%2F978-3-319-42294-7_66
https://link.springer.com/chapter/10.1007/978-3-319-42294-7_66/fulltext.html

Diversifying Investments and Maximizing Sharpe Ratio: A Novel Quadratic Unconstrained Binary Optimization Formulation

Authors: Mirko Mattesi Luca Asproni Christian Mattia et al.

Source: Quantum Reports, Vol 6, Iss 2, Pp 244-262 (2024)

Subject Terms: portfolio optimization, quantum annealing, QUBO, quantum computing, Sharpe Ratio, diversification, Physics, QC1-999

File Description: electronic resource

Relation: https://www.mdpi.com/2624-960X/6/2/18; https://doaj.org/toc/2624-960X

Access URL: https://doaj.org/article/dc28298c864d48c9a28670d84293fb6e

Experiments on Neighborhood Combination Strategies for Bi-objective Unconstrained Binary Quadratic Programming Problem

Authors: Qing-Xian Wang Wei An Mingsheng Shang et al.

Source: Communications in Computer and Information Science ISBN: 9789811064418

Access URL: https://link.springer.com/chapter/10.1007/978-981-10-6442-5_42
https://rd.springer.com/chapter/10.1007/978-981-10-6442-5_42

An Effective Genetic Algorithm with Uniform Crossover for Bi-objective Unconstrained Binary Quadratic Programming Problem.

Authors: Huo, Chao Zeng, Rong-Qiang Wang, Yang et al.

Source: Intelligent Data Engineering & Automated Learning - IDEAL 2016; 2016, p58-67, 10p

A Multi-parent Crossover Based Genetic Algorithm for Bi-Objective Unconstrained Binary Quadratic Programming Problem.

Authors: Huo, Chao Zeng, Rongqiang Wang, Yang et al.

Source: Bio-inspired Computing - Theories & Applications: 11th International Conference, BIC-TA 2016, Xi'an, China, October 28-30, 2016, Revised Selected Papers, Part II; 2016, p10-19, 10p

Solving Bi-objective Unconstrained Binary Quadratic Programming Problem with Multi-objective Backbone Guided Search Algorithm.

Authors: Xue, Li-Yuan Zeng, Rong-Qiang Wang, Yang et al.

Source: Intelligent Computing Theories & Application: 12th International Conference, ICIC 2016, Lanzhou, China, August 2-5, 2016, Proceedings, Part II; 2016, p745-753, 9p

An Effective Genetic Algorithm with Uniform Crossover for Bi-objective Unconstrained Binary Quadratic Programming Problem

Authors: Ming-Sheng Shang Rong-Qiang Zeng Chao Huo et al.

Source: Lecture Notes in Computer Science ISBN: 9783319462561

Access URL: https://rd.springer.com/chapter/10.1007/978-3-319-46257-8_7
https://doi.org/10.1007/978-3-319-46257-8_7
https://link.springer.com/chapter/10.1007%2F978-3-319-46257-8_7

A Multi-parent Crossover Based Genetic Algorithm for Bi-Objective Unconstrained Binary Quadratic Programming Problem

Authors: Yang Wang Chao Huo Rong-Qiang Zeng et al.

Source: Communications in Computer and Information Science ISBN: 9789811036132

Access URL: https://dblp.uni-trier.de/db/conf/bic-ta/bic-ta2016-2.html#HuoZWS16
https://link.springer.com/10.1007/978-981-10-3614-9_2
https://link.springer.com/chapter/10.1007/978-981-10-3614-9_2
https://rd.springer.com/chapter/10.1007/978-981-10-3614-9_2

Walsh-based surrogate-assisted multi-objective combinatorial optimization: A fine-grained analysis for pseudo-boolean functions.

Authors: Derbel, Bilel Pruvost, Geoffrey Liefooghe, Arnaud et al.

Source: Applied Soft Computing. Mar2023, Vol. 136, pN.PAG-N.PAG. 1p.

Subject Terms: Combinatorial optimization, Quadratic programming, Benchmark problems (Computer science), Landscape design, Bilevel programming

Multiobjective Binary ACO for Unconstrained Binary Quadratic Programming.

Authors: Souza, Murilo Zangari de Pozo, Aurora Trinidad Ramirez

Source: 2015 Brazilian Conference on Intelligent Systems (BRACIS); 2015, p86-91, 6p

Applying Ising Machines to Multi-objective QUBOs

Authors: Ayodele, Mayowa Allmendinger, Richard López-Ibáñez, Manuel et al.

Index Terms: Computer Science - Artificial Intelligence, Quantum Physics, G.1.6, text

URL: http://arxiv.org/abs/2305.11648

Experiments on Local Search for Bi-objective Unconstrained Binary Quadratic Programming.

Authors: Liefooghe, Arnaud Verel, Sébastien Paquete, Luís et al.

Source: Evolutionary Multi-Criterion Optimization 8th International Conference, EMO 2015, Guimarães, Portugal, March 29 --April 1, 2015. Proceedings, Part I; 2015, p171-186, 16p

Multi-objectivization Inspired Metaheuristics for the Sum-of-the-Parts Combinatorial Optimization Problems

Authors: Shi, Jialong Sun, Jianyong Zhang, Qingfu

Index Terms: Computer Science - Neural and Evolutionary Computing, text

URL: http://arxiv.org/abs/1911.04658

Applying Ising Machines to Multi-objective QUBOs

Authors: Mayowa Ayodele Richard Allmendinger Manuel López-Ibáñez et al.

Contributors: Mayowa Ayodele Richard Allmendinger Manuel López-Ibáñez et al.

Source: Ayodele, M, Allmendinger, R, López-Ibáñez, M, Liefooghe, A & Parizy, M 2023, Applying Ising Machines to Multi-objective QUBOs. in GECCO '23 Companion: Proceedings of the Companion Conference on Genetic and Evolutionary Computation. Association for Computing Machinery, pp. 2166-2174. https://doi.org/10.1145/3583133.3596312

Subject Terms: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], FOS: Computer and information sciences, Quantum Physics, Digital annealer, Multi-objective Optimisation, QUBO, Digital Annealer, Computer Science - Artificial Intelligence, G.1.6, 0211 other engineering and technologies, FOS: Physical sciences, Scalarisation, 02 engineering and technology, UBQP, [INFO.INFO-RO] Computer Science [cs]/Operations Research [math.OC], Aggregation, Artificial Intelligence (cs.AI), Multi-objective optimisation, 0202 electrical engineering, electronic engineering, information engineering, Quantum Physics (quant-ph)

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Access URL: http://arxiv.org/abs/2305.11648
https://research.manchester.ac.uk/en/publications/447ccd96-701d-4552-8054-2166d954ea9f
https://doi.org/10.1145/3583133.3596312
https://hal.science/hal-04169849v1/document
https://doi.org/10.1145/3583133.3596312
https://hal.science/hal-04169849v1
http://www.scopus.com/inward/record.url?scp=85169041172&partnerID=8YFLogxK
https://research.manchester.ac.uk/en/publications/447ccd96-701d-4552-8054-2166d954ea9f
https://doi.org/10.1145/3583133.3596312
https://www.mendeley.com/catalogue/b0dcf433-318e-392d-8146-d91908be4915/