Addressing the importance of the algorithm design process, Deterministic Operations Research focuses on the design of solution methods for both continuous and discrete linear optimization problems.

Kanti Swarup, Linear Fractional Functionals Programming, Operations Research, Vol. 13, No. 6 (Nov. - Dec., 1965), pp. 1029-1036 ...

Ron Shamir, Probabilistic Analysis in Linear Programming, Statistical Science, Vol. 8, No. 1, Report from the Committee on Applied and Theoretical Statistics of the National Research Council on ...

Inverse optimisation and linear programming have emerged as crucial instruments in addressing complex decision-making problems where underlying models must be inferred from observed behaviour.

[1] Recent contributions to linear semi-infinite optimization: an update. Annals of Operations Research (2018). [2] Recent advances in nonconvex semi-infinite programming: Applications and algorithms.

In 1991, linear programming was thought to be a mature field. From 1991 through 1998, linear programming performance improved dramatically.

Roth, A. E., U. G. Rothblum, and J. H. Vande Vate. "Stable Matchings, Optimal Assignments, and Linear Programming." Mathematics of Operations Research 18, no. 4 ...

An introduction to a range of Operations Research techniques, covering: foundations of linear programming, including the simplex method and duality; integer programming; markov chains; queueing theory ...

Marshall, Paul W. "Linear Programming: A Technique for Analyzing Resource Allocation Problems." Harvard Business School Background Note 171-322, January 1971. (Revised November 1975 ...

Understand mathematical tools for strategic decision-making prevalent in several industries. Identify, model, and solve problems that relate to optimisation, two-player games, or stochastic processes.