Multi-level stochastic approximation algorithms

Multi-level stochastic approximation algorithms

Approximation Algorithms for 2-stage and Multi-stage Stochastic Optimization

Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizations of the data. We consider the well-studied paradigm of stochastic recourse models, in which the realized input is revealed through a series of stages and one can take decisions in each stage in response to the new in...

Approximation algorithms for stochastic orienteering

In the Stochastic Orienteering problem, we are given a metric, where each node also has a job located there with some deterministic reward and a random size. (Think of the jobs as being chores one needs to run, and the sizes as the amount of time it takes to do the chore.) The goal is to adaptively decide which nodes to visit to maximize total expected reward, subject to the constraint that the...

Consensus - Type Stochastic Approximation Algorithms

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Multi-organization scheduling approximation algorithms

In this paper we consider the problem of scheduling on computing platforms composed of several independent organizations, known as the Multi-Organization Scheduling Problem (MOSP). Each organization provides both resources and jobs and follows its own objectives. We are interested in the best way to minimize the makespan on the entire platform when the organizations behave in a selfish way. We ...