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Operations Research 3.0 Adds Reinforcement Learning and Improved Shortest Path Algorithms

Published January 17, 2003

January 17, 2003–The new Operations Research 3.0 application package provides business professionals and students with even more tools for solving problems in linear optimization, quadratic programming, and combinatorial optimization–with heuristic routines for the hardest of these instances. The updated product also offers new methods for shortest path tasks and reinforcement learning.

Operations Research consists of five component packages, one of which is completely new in this version. It addresses the topic of reinforcement learning, a relatively new method for stochastic optimization and control that is quite powerful for certain types of problems. The package on shortest path tasks has also been completely rewritten for Version 3.0. It includes a new, very efficient, point-to-point routing algorithm as well as an improved implementation of Dijkstra’s algorithm.

The chapter on combinatorial optimization has been enlarged in Version 3.0 by implementing more heuristics, notably tabu search, while the comprehensive documentation and selection of example notebooks has been expanded. Each problem is explained, modeled, and solved in full detail.

For more information, refer to the Operations Research product pages.