View on Coursera Course Description This course continues our data structures and algorithms specialization by focussing on the use of linear and integer programming formulations for solving ...

In the present paper a bi-objective integer linear programming problem (BILP) is discussed. The main effort in this work is to effectively implement the ϵ-constraint method to produce a complete set ...

Specialization: Data Science Foundations: Data Structures and Algorithms Instructor: Sriram Sankaranarayanan, Assistant Professor Prior knowledge needed: We highly recommended successfully completing ...

We present two first-order primal-dual algorithms for solving saddle point formulations of linear programs, namely FWLP (Frank-Wolfe Linear Programming) and FWLP-P. The former iteratively applies the ...

The Dynamic programming track before detect (DP-TBD) algorithm has been widely used for detection and tracking of weak targets. The selection of the merit function has an immediate influence on the ...

On Dantzig-Wolfe Decomposition in Integer Programming and Ways to Perform Branching in a Branch-And-Price Algorithm, Operations Research, Vol. 48, No. 1 (Jan. - Feb., 2000), pp. 111-128 ...

Technical Terms Probabilistic Programming: A programming paradigm that incorporates probabilistic models within code, enabling the direct representation and manipulation of uncertainty.

Mining frequent item sets from a large dense type database may generate a large number of frequent item sets, and it may generate redundant information in some cases. To address these problems, a ...