Scenario Decomposition for 0-1 Stochastic Programs: Improvements and Asynchronous Implementation

A recently proposed scenario decomposition algorithm for stochastic 0-1 programs finds an optimal solution by evaluating and removing individual solutions that are discovered by solving scenario subproblems. In this work, we develop an asynchronous, distributed implementation of the algorithm which has computational advantages over existing synchronous implementations of the algorithm. Improvements to both the synchronous and asynchronous algorithm are proposed. We test the results on well known stochastic 0-1 programs from the SIPLIB test library and are able to solve previously unsolved instances from the test set.

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