Relevant bibliographies by topics / Pareto

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  1. Journal articles

Academic literature on the topic 'Pareto'

Author: Grafiati
Published: 4 June 2021
Last updated: 13 June 2025

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Journal articles on the topic "Pareto"

1

Wei, Xin. "Multi-Objective Optimization Base on Incremental Pareto Fitness." Advanced Materials Research 1030-1032 (September 2014): 1733–36. http://dx.doi.org/10.4028/www.scientific.net/amr.1030-1032.1733.

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A new multi-objective optimization algorithm based on incrementally Pareto fitness is proposed in this paper. To overcome the directly calculate the Pareto fitness matrix expensively, we adopt to make full use of information of last iteration at each stept to update the Parteto fitness matrix gradually. Experiments proved the highest efficiency of the new method.
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2

Mornati, Fiorenzo. "Pareto Optimality in the work of Pareto." Revue européenne des sciences sociales, no. 51-2 (December 15, 2013): 65–82. http://dx.doi.org/10.4000/ress.2517.

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3

Németh, A. B. "Between Pareto efficiency and Pareto ε-efficiency". Optimization 20, № 5 (1989): 615–37. http://dx.doi.org/10.1080/02331938908843483.

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4

Busino, Giovanni. "Pareto oggi." Revue européenne des sciences sociales, no. XLVIII-146 (July 1, 2010): 113–27. http://dx.doi.org/10.4000/ress.761.

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5

Yeh, Hsiaw-Chan, Barry C. Arnold, and Christopher A. Robertson. "Pareto processes." Journal of Applied Probability 25, no. 2 (1988): 291–301. http://dx.doi.org/10.2307/3214437.

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An autoregressive process ARP(1) with Pareto-distributed inputs, analogous to those of Lawrance and Lewis (1977), (1980), is defined and its properties developed. It is shown that the stationary distributions are Pareto. Further, the maximum and minimum processes are asymptotically Weibull, and the ARP(1) process is shown to be closed under maximization or minimization when the number of terms is geometrically distributed. The ARP(1) process leads naturally to an extremal process in the sense of Lamperti (1964). Statistical inference for the ARP(1) process is developed. An absolutely continuous variant of the Pareto process is described.
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6

Makatura, Liane, Minghao Guo, Adriana Schulz, Justin Solomon, and Wojciech Matusik. "Pareto gamuts." ACM Transactions on Graphics 40, no. 4 (2021): 1–17. http://dx.doi.org/10.1145/3476576.3476758.

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7

Makatura, Liane, Minghao Guo, Adriana Schulz, Justin Solomon, and Wojciech Matusik. "Pareto gamuts." ACM Transactions on Graphics 40, no. 4 (2021): 1–17. http://dx.doi.org/10.1145/3450626.3459750.

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8

Yeh, Hsiaw-Chan, Barry C. Arnold, and Christopher A. Robertson. "Pareto processes." Journal of Applied Probability 25, no. 02 (1988): 291–301. http://dx.doi.org/10.1017/s0021900200040936.

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An autoregressive process ARP(1) with Pareto-distributed inputs, analogous to those of Lawrance and Lewis (1977), (1980), is defined and its properties developed. It is shown that the stationary distributions are Pareto. Further, the maximum and minimum processes are asymptotically Weibull, and the ARP(1) process is shown to be closed under maximization or minimization when the number of terms is geometrically distributed. The ARP(1) process leads naturally to an extremal process in the sense of Lamperti (1964). Statistical inference for the ARP(1) process is developed. An absolutely continuous variant of the Pareto process is described.
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9

Ikefuji, Masako, Roger J. A. Laeven, Jan R. Magnus, and Chris Muris. "Pareto utility." Theory and Decision 75, no. 1 (2012): 43–57. http://dx.doi.org/10.1007/s11238-012-9293-8.

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10

Green, M. W., and B. C. Arnold. "Pareto Distributions." Applied Statistics 35, no. 2 (1986): 215. http://dx.doi.org/10.2307/2347273.

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