AHARON BEN-TAL

"For an optimization problem under uncertainty, the real problem is to offer models for which the user can provide the data, and the optimizer can solve efficiently the resulting mathematical programming problem, including dynamical ones. RO methodology was aimed to address these challenges right from the start and is the reason why it is so widely adopted. "

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MOR Papers by This Author

Barzilai J, Ben-Tal A (1981) A nonorthogonal Fourier expansion for conic decomposition. Math. Oper. Res. 6(3):363–373.

Ben-Tal A, Nemirovski A, Roos C (2003) Extended matrix cube theorems with applications to μ-theory in control. Math. Oper. Res. 28(3):497–523.

Ben-Tal, A (1985) The entropic penalty approach to stochastic programming. Math. Oper. Res. 10(2): 263–279.

Ben-Tal A, Teboulle M (1987) Penalty functions and duality in stochastic programming via ф-divergence functionals. Math. Oper. Res. 12(2):224–240.

Ben-Tal A, Nemirovski A (2001) On polyhedral approximations of the second-order cone. Math. Oper. Res. 26(2):193–205.

Ben-Tal A, Nemirovski A (2009) On safe tractable approximations of chance-constrained linear matrix inequalities. Math. Oper. Res. 34(1):1–25.

ALVIN E. ROTH

"Marketplaces are tools that people use to help us coordinate and compete and organize ourselves to mutual benefit. But to do that well, marketplaces have to attract people to participate (i.e. to make a thick market), they have to help participants deal with the congestion that can arise when the market is thick enough to have lots of transactions that can potentially be considered, and they have to make the market safe to participate in. The ‘magic of the market’ doesn’t happen by magic, so there are lots of markets that don’t work well, and that don’t produce the benefits that they could. Proposing new rules for existing marketplaces, or new marketplaces, can sometimes help that along. Of course, market conditions change, and the behavior of participants change, so markets have to be monitored and changed themselves when they stop doing what we want them to do."

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MOR Papers by This Author

Roth AE (1976) Subsolutions and the Supercore of Cooperative Games. Math. Oper. Res. 1(1):43–49.

Roth AE (1977) Individual rationality and Nash’s solution to the bargaining problem. Math. Oper. Res. 2(1): 64–65.

Roth AE (1982) The economics of matching: Stability and incentives. Math. Oper. Res. 7(4):617–628.

Roth AE (1985) Conflict and coincidence of interest in job matching: Some new results and open questions. Math. Oper. Res. 10(3):379–389.

Roth AE, Rothblum UG, Vande Vate, JH (1993) Stable matchings, optimal assignments, and linear programming. Math. Oper. Res. 18(4): 803–828.

JEAN BERNARD LASSERRE

"One important (if not unique) goal of OR is to help solve practical problems with tools from applied mathematics, probability, statistics, and so forth. However, the focus now seems to be much more on “applications” than on “disciplines.” For instance “LP” [linear programming] and “Integer Programming” were two important flagships of OR, whereas now “Communication and Energy Networks” or the more fuzzy “Machine Learning,” “Deep Learning,” and “Big Data” are in the front of the scene."

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MOR Papers by This Author

Lasserre JB (2002) Semidefinite programming vs. LP relaxations for polynomial programming. Math. Oper. Res. 27(2):347-360.

Lasserre JB (2013) Inverse polynomial optimization. Math. Oper. Res. 28(3):418-436.

Lasserre JB, Zeron ES (2002) An alternative algorithm for counting lattice points in a convex polytope.Math. Oper. Res. 30(3):597-614.

Lasserre J, Zeron ES (2002) On counting integral points in a convex rational polytope. Math. Oper. Res. 28(4):853-870.

Riener C, Theobald T, Andrén LJ, Lasserre JB (2012) Exploiting symmetries in SDP-relaxations for polynomial optimization. Math. Oper. Res. 38(1):122-141.