Abstract: A Quantum Genetic Based Scheduling Algorithm (QGBSA) for stochastic flow shop scheduling with random breakdown and random repair time is proposed in this paper, which combines stochastic programming and stochastic simulation theory, quantum compute and genetic algorithm together. In the QGBSA, the Q-bit based representation in discrete 0-1 hyperspace is employed, which is then convert...

Stochastic scheduling of parallel systems is a recent research area in computer science as well as in operations research. The problem under consideration in this chapter is the scheduling of parallel computations which are modeled by task graphs in multiprocessor systems. The particularity of this study is that task running times are assumed to be random variables, instead of known constants a...

This paper describes a complete and efficient solution to the stochastic allocation and scheduling for Multi-Processor System-on-Chip (MPSoC). Given a conditional task graph characterizing a target application and a target architecture with alternative memory and computation resources, we compute an allocation and schedule minimizing the expected value of communication cost, being the communica...

This paper describes a complete and efficient solution to the stochastic allocation and scheduling for Multi-Processor System-on-Chip (MPSoC). Given a conditional task graph characterizing a target application and a target architecture with alternative memory and computation resources, we compute an allocation and schedule minimizing the expected value of communication cost, being the communica...

In this paper, we study the joint routing-scheduling problem in energy harvesting communication networks. Our policies, which are based on stochastic subgradient methods on the dual domain, act as an energy harvesting variant of the stochastic family of backpresure algorithms. Specifically, we propose two policies: (i) the Stochastic Backpressure with Energy Harvesting (SBP-EH), in which a node...

A principal goal of this dissertation is to study stochastic optimization and real-time scheduling in cyber-physical systems (CPSs) ranging from realtime wireless systems to energy systems to distributed control systems. Under this common theme, this dissertation can be broadly organized into three parts based on the system environments. The first part investigates stochastic optimization in re...

Stochastic flexible flow shop scheduling problem (SFFSSP) is one the main focus of researchers due to the complexity arises from inherent uncertainties and also the difficulty of solving such NP-hard problems. Conventionally, in such problems each machine’s job process time may encounter uncertainty due to their relevant random behaviour. In order to examine such problems more realistically, fi...