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Quantum and quantum-inspired optimisation algorithms are designed to solve problems represented in binary, quadratic and unconstrained form.
Assignment problems and the location of economic activities
Tjalling C. Koopmans and Martin J. Beckmann · 1957
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The use of reference objectives in multiobjective optimisation
Andrzej P. Wierzbicki · 1980
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QAPLIB–a quadratic assignment problem library
Rainer E. Burkard, Stefan E. Karisch, and Franz Rendl · 1997
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Heuristic algorithms for the unconstrained binary quadratic programming problem
John E. Beasley · 1998
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Handling preferences in evolutionary multiobjective optimization: A survey
Carlos A. Coello Coello · 2000
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Multi-Objective Optimization Using Evolutionary Algorithms
Kalyanmoy Deb · 2001
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Inferential performance assessment of stochastic optimisers and the attainment function
Viviane Grunert da Fonseca, Carlos M. Fonseca, and Andreia O. Hall · 2001
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Instance generators and test suites for the multiobjective quadratic assignment problem
Joshua D. Knowles and David Corne · 2003
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Pareto local optimum sets in the biobjective traveling salesman problem: An experimental study
Luís Paquete, Marco Chiarandini, and Thomas Stützle · 2004
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Hybrid population-based algorithms for the bi-objective quadratic assignment problem
Manuel López-Ibáñez, Luís Paquete, and Thomas Stützle · 2006
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Using experimental design to analyze stochastic local search algorithms for multiobjective problems
Luís Paquete, Thomas Stützle, and Manuel López-Ibáñez · 2007
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Routing and wavelength assignment with protection: A QUBO and digital annealer approach
Oylum Şeker, Merve Bodur, and Hamed Pouya · 2008
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Quality assessment of Pareto set approximations
Eckart Zitzler, Joshua D. Knowles, and Lothar Thiele · 2009
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Exploratory analysis of stochastic local search algorithms in biobjective optimization
Manuel López-Ibáñez, Luís Paquete, and Thomas Stützle · 2010
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On sequential online archiving of objective vectors
Manuel López-Ibáñez, Joshua D. Knowles, and Marco Laumanns · 2011
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Digital annealer for quadratic unconstrained binary optimization: a comparative performance analysis
Oylum Şeker, Neda Tanoumand, and Merve Bodur · 2012
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Item listing optimization for e-commerce websites based on diversity
Naoki Nishimura, Kotaro Tanahashi, Koji Suganuma, Masamichi J. Miyama, and Masayuki Ohzeki · 2019
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Multiobjective simulated annealing: Principles and algorithm variants
Khalil Amine · 2019
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On modeling local search with special-purpose combinatorial optimization hardware
Xiaoyuan Liu, Hayato Ushijima-Mwesigwa, Avradip Mandal, Sarvagya Upadhyay, Ilya Safro, and Arnab Roy · 2019
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Penalty and partitioning techniques to improve performance of QUBO solvers
Amit Verma and Mark Lewis · 2020
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The d-wave advantage system: An overview, 2020
Catherine McGeoch and Pau Farre · 2020
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Ising formulations of many NP problems
Andrew Lucas · 2014
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The unconstrained binary quadratic programming problem: a survey
Gary A. Kochenberger, Jin-Kao Hao, Fred Glover, Mark Lewis, Zhipeng Lü, Haibo Wang, and Yang Wang · 2014
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Anytime Pareto local search
Jérémie Dubois-Lacoste, Manuel López-Ibáñez, and Thomas Stützle · 2014
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Experiments on local search for bi-objective unconstrained binary quadratic programming
Arnaud Liefooghe, Sébastien Verel, Luís Paquete, and Jin-Kao Hao · 2015
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Demonstration of a scaling advantage for a quantum annealer over simulated annealing
Tameem Albash and Daniel A. Lidar · 2018
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Physics-inspired optimization for quadratic unconstrained problems using a digital annealer
Maliheh Aramon, Gili Rosenberg, Elisabetta Valiante, Toshiyuki Miyazawa, Hirotaka Tamura, and Helmut G Katzgraber · 2019
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Satoshi Matsubara, Motomu Takatsu, Toshiyuki Miyazawa, Takayuki Shibasaki, Yasuhiro Watanabe, Kazuya Takemoto, and Hirotaka Tamura · 2020
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pymoo: Multi-objective optimization in python
J. Blank and K. Deb · 2020
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Third generation digital annealer technology, 2021
Nakayama Hiroshi, Koyama Junpei, Yoneoka Noboru, and Miyazawa Toshiyuki · 2021
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Solving QUBO with GPU parallel MOPSO
Noriyuki Fujimoto and Kouki Nanai · 2021
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Portfolio optimisation using the d-wave quantum annealer
Frank Phillipson and Harshil Singh Bhatia · 2021
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Penalty weights in QUBO formulations: Permutation problems
Mayowa Ayodele · 2022
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